# Expanded AI-assisted art research library

Compiled 31 October 2026; claim/access audit 3 November 2026. **67 distinct source URLs**, across 20 artist/process accounts, 10 books/catalogues, 9 institutional/journal/course resources, 20 workflows/papers and 8 additional frameworks/context sources. These are source records, not 67 independent tools or 67 methods tested in the studio. All 67 URLs were absent from the earlier top-level Kochu research notes; that is a link-level comparison, not a claim that every topic was previously unknown.

**Evidence:** 66 source pages/documents/abstracts opened; 1 historical course record is search-only and explicitly closed. 36 entries contain substantial process/method material, 28 are partial records and 3 are mainly contextual/showcase records. Publisher descriptions, accessible text and failed retrieval are distinguished in each entry. No complete-book reading, model execution, training, hardware trial or video playback is implied by a page being opened.

See the [67-record accuracy audit and three proposed experiments](../research-audit-2026-11-03/README.md). Original compilation notes are retained in the audit snapshot.

Open the [searchable library](http://127.0.0.1:4387/art-research-library/), or use this Markdown document, `sources.csv` and `sources.json`. The original prototypes and their artist-feedback archive remain separate from this research expansion.

## A useful first reading path

Start with **David Salle (ART02)**, **WangShui (ART01)**, **Helena Sarin (ART03)** and **Scott Eaton (ART04)**. These account for generated imagery passing through selection, drawing, paint, editing, fabrication or an artist book. They are closer to a painter's material practice than another screen treatment. Their exact model recipes and requirements differ; these are examples to learn from, not guaranteed recipes for Iana.

For broader thinking, read **Artificial Aesthetics (LIT02)**, inspect **The Practice of Art and AI (LIT07)** and **Digital Art: 1960s to Now (LIT08)**, and use **Creative AI Lab (LIT11)** to find software/process walkthroughs. Some books are publisher records rather than retrieved complete text. The author-hosted Artificial Aesthetics PDF was opened; its 2024 citation and January 2025 compiled-PDF date are recorded rather than conflated.

For a bounded practical investigation, compare **Invoke Canvas (LAB01)** and **ComfyUI inpainting (LAB02)**, then use **SDEdit (LAB06)** to understand the tension between input structure and generated variation. **PromptPaint (LAB15)** and **Collaborative Neural Painting (LAB16)** are useful interaction precedents with explicit research/deployment limitations. No current local installation is certified.

For physical output and co-painting, investigate **FRIDA/CoFRIDA (LAB17/LAB18)**, **e-David (CTX03)** and **Diffusion Illusions (LAB19)**. These span specialist robotic painting and printable optical objects; they do not establish an off-the-shelf substitute for an artist's studio.

For understanding whether an interaction actually gives the artist agency, use **COFI (CTX02)** and **Fiebrink's education study (CTX05)**. A visual system should be assessed through the artist's ability to choose, correct and redirect it, not only model novelty. This is our interpretation of the sources, not an outcome measured with Iana.

## What this expansion changes

The earlier survey leaned toward rendering mechanisms. This library broadens the scope to material painting, drawing, screenprint, ceramics, wet-plate photography, sculpture, artist books, film, archives, datasets, community participation and literary/sound practices. The latter are marked as adjacent when they are not painting workflows.

The strongest new direction for further investigation is **AI as an intermediate stage in an authored practice**: selected material enters a controlled model process; the artist edits, rejects, redraws or translates it into an object. That is a proposed research emphasis, not a requirement that Iana use AI or accept any result. No aesthetic fit is inferred from technical capability.

This is a substantially larger annotated discovery pass. It remains incomplete as a systematic literature review or evaluation of model quality, colour/material fidelity, present-day runtime compatibility and an artist-directed studio experiment.

## How to use the records

- **Opened**: linked page, document, abstract or publisher record was retrieved, with the specific access scope stated.
- **Search-only**: target was not read directly; description comes from indexed extraction and is qualified.
- **Detailed**: source has substantial process/method information. It does not mean a ready-to-run, fully licensed, compatible package.
- **Partial**: useful conceptual/process description or publication metadata with missing implementation/fulltext detail.
- **Showcase**: a contextual work/exhibition record with limited production detail.
- **Practical use**: our interpretation for study or experimentation, kept separate from the source's documented claims.

## Artists and processes

### ART01 — Painting as a recursive feedback loop: Isle of Vitr∴ous

**WangShui; interview by Sarah Cascone** · 2022 · firsthand interview

[Source](https://news.artnet.com/art-world/wangshui-whitney-biennial-ai-2113270) · Evidence: opened · Process depth: detailed

Medium: oil on abraded aluminium. AI produces new images from previous paintings. WangShui sketches, collages and abrades those images into metal, adds thin oil layers, and improvises throughout; programmers collaborate on the systems.

**Practical use:** A generated image can be an intermediate drawing that an artist materially transforms.

**Access:** free interview text opened

**Limits:** The painting workflow is explicit; its exact model and training recipe are not. Process relevance does not establish aesthetic fit.

Tags: painting, oil, aluminium, drawing, collage, human finishing, recursive workflow.

### ART02 — How I taught an AI to think like a painter

**David Salle; with technologist Grant Davis** · 2025 · artist process

[Source](https://mail.davidsallestudio.net/%2725%20Financial%20Times_How%20I%20Taught%20AI_May.pdf) · Evidence: opened · Process depth: detailed

Medium: paintings over printed canvas backgrounds. Salle describes staged training-data choices and an image-variation control in Wand. He selects promising generated scenes, prints them onto canvas, and paints figurative layers over them.

**Practical use:** Separate the generated underlayer from the artist's decisions about edges, colour, composition and painted intervention.

**Access:** free studio-hosted PDF; six pages opened

**Limits:** His account includes other painters in early training, then his own work. It is not proof that five photographs suffice.

Tags: painting, canvas, printed underlayer, human finishing, artist archive, Wand.

### ART03 — Art and Software Run as Parallel Tracks in the Life of Helena Sarin

**Helena Sarin; AOTM interview** · 2022 · firsthand interview

[Source](https://aotm.gallery/art-and-software-run-as-parallel-tracks-in-the-life-of-helena-sarin/) · Evidence: opened · Process depth: detailed

Medium: artist books and ceramics. Sarin trains models on her art and photography, extends pipelines through post-processing, and edits images into books. She describes potteryGAN as returning digital AI designs to physical artifacts.

**Practical use:** Treat generation, editing, sequencing and making an object as separate authored stages.

**Access:** free interview page opened

**Limits:** The interview explains the overall pipeline; it does not provide a reproducible clay construction, glaze or firing recipe.

Tags: ceramics, artist book, GAN, own photographs, post-processing, physical output.

### ART04 — Human Allocation of Space and Figures: documented drawing-to-object processes

**Scott Eaton** · 2019 works; page undated · artist process

[Source](https://www.nvidia.com/en-us/research/ai-art-gallery/artists/scott-eaton/) · Evidence: opened · Process depth: detailed

Medium: hand drawing, archival prints and bronze. Custom GANs translate Eaton's drawings into rendered bodies or geometric volumes. He authors source photography and detailed drawings; sculpture output is converted to polygons, printed, moulded and cast.

**Practical use:** A clear hand-drawn structure can remain central while a learned system supplies a different representational layer.

**Access:** free artist presentation opened

**Limits:** Figurative/anatomical methods do not establish abstract-painting fidelity; substantial custom datasets and fabrication are involved.

Tags: drawing, photography, bronze, print, image-to-image, human structure.

### ART05 — Shared Visual Abstractions

**Tom White** · 2019 · artist process

[Source](https://arxiv.org/html/1912.04217v1) · Evidence: opened · Process depth: detailed

Medium: abstract ink prints. A constrained drawing system searches stroke placement, thickness and colour using responses from trained image classifiers. White designs the drawing vocabulary and experiments; photographs of physical prints test recognition across models.

**Practical use:** Restricting marks and colours can be an artistic decision, independent of a generator's realism.

**Access:** open paper; HTML methods opened

**Limits:** The paper measures classifier responses and a small human label-matching survey; neither measures beauty or usefulness to Iana.

Tags: abstraction, ink print, constraints, classifier feedback, research paper.

### ART06 — In Silico / Technical Images

**Casey Reas; Erika Weitz on Technical Images** · 2024–2025 works · artist process

[Source](https://reas.com/in-silico) · Evidence: opened · Process depth: detailed

Medium: wet-plate collodion photographs, aluminium prints and software. Reas curates plant scans, microscopy and landscape imagery for GAN training and selects outputs. With Weitz, generated images become collodion plates; RGB channels are separately photographed and recombined.

**Practical use:** Physical translation and channel-level recomposition can contribute as much as image synthesis.

**Access:** free artist process page opened

**Limits:** Botanical imagery is contextual here, not an aesthetic recommendation. The page documents stages without a complete executable workflow.

Tags: photography, collodion, aluminium, physical output, dataset curation, GAN.

### ART07 — Fall of the House of Usher I and II

**Anna Ridler** · 2017 · institutional project

[Source](https://dam.org/museum/artists_ui/artists/ridler-anna/fall-house-usher/) · Evidence: opened · Process depth: partial

Medium: ink drawing dataset and animation. Ridler makes more than 200 drawings after the 1929 film; interconnected GANs generate stills and feedback material for subsequent training sets. The handmade dataset is also an exhibited work.

**Practical use:** Preparatory drawings and dataset construction can remain visible parts of the finished project.

**Access:** free museum page; artist-authored text opened

**Limits:** This is intentionally horror/uncanny work, included for process rather than its aesthetic; implementation details are limited.

Tags: drawing, ink, animation, handmade dataset, archive, horror aesthetic.

### ART08 — My Artificial Muse

**Albert Barqué-Duran, Mario Klingemann and Marc Marzenit** · 2017 documented Sónar+D performance; current project-page body says 2016 · artist process

[Source](https://albert-data.com/pages/my-artificial-muse) · Evidence: opened · Process depth: partial

Medium: live oil painting, projected neural generation and sound. A neural network produces a classical-style image; Barqué-Duran interprets it in paint. Embodied sensors connect his movement with a generative soundscape.

**Practical use:** Painting can be a selective human interpretation of an AI proposal, rather than a literal transfer.

**Access:** free artist project page opened

**Limits:** The current project page inconsistently says 2016 and 2017; a collaborator account and the artist exhibition list document a 2017 performance. The inception/premiere conflict remains unresolved. Model settings and a painting recipe are absent.

Tags: oil painting, performance, human interpretation, neural generation, sound.

### ART09 — Reflection: cameras and physical feedback in robotic painting

**Pindar Van Arman; artist-hosted essay by centoshi** · Date not established · artist process

[Source](https://www.vanarman.com/reflection) · Evidence: opened · Process depth: detailed

Medium: paintings on stretched canvas. Cameras observe marks and multiple algorithms evaluate the changing image before the robot makes further marks. Physical paint variation becomes input; Van Arman authors and revises the robotic system.

**Practical use:** The material surface can feed back into computational decisions instead of merely receiving a finished digital image.

**Access:** free artist-hosted process essay opened

**Limits:** Claims about machine creativity are the artists' interpretation. The page does not supply a reproducible control implementation.

Tags: painting, robotics, camera feedback, physical material, canvas.

### ART10 — Tabula Rasa: an artist's account of training on solid colours

**David Young** · 2019 original essay · artist process

[Source](https://writings.davidyoung.art/tabula-rasa/) · Evidence: opened · Process depth: detailed

Medium: abstract generated images. Young begins GAN training with one black image, then adds further solid colours and observes resulting textures, grids and shapes. He authors the restricted material and compares stages of the system's development.

**Practical use:** An AI investigation can begin with colour and compositional constraints, without imitating a painter's complete style.

**Access:** free artist essay opened

**Limits:** Machine emotion is an acknowledged metaphor, not a demonstrated mental state; the essay is not a current software tutorial.

Tags: abstraction, colour, minimal dataset, GAN, artist essay.

### ART11 — Hallucinations / Adversarially Evolved Hallucinations

**Trevor Paglen** · 2017 works; 2020 page · artist process

[Source](https://paglen.studio/2020/04/09/hallucinations/) · Evidence: opened · Process depth: partial

Medium: synthetic images and dye-sublimation prints. Paglen constructs training categories from literature, history and other conceptual corpora, trains recognition systems, then uses adversarial generation to produce images satisfying those systems.

**Practical use:** Choosing what categories a system can recognise can be a substantive part of the artwork's argument.

**Access:** free artist page opened

**Limits:** The artist explains the conceptual pipeline; architecture and training details are absent. Some imagery is disturbing.

Tags: print, dataset authorship, classification, GAN, critical practice.

### ART12 — Zizi — Queering the Dataset

**Jake Elwes** · 2019 · artist process

[Source](https://www.jakeelwes.com/project-zizi-2019.html) · Evidence: opened · Process depth: partial

Medium: multichannel video. Elwes retrains a StyleGAN model originally trained on FFHQ with 1,000 additional images of drag and gender-fluid faces. Dataset intervention changes the model's visual vocabulary; Elwes authors framing and installation.

**Practical use:** Dataset additions can deliberately challenge what a pretrained model treats as normal.

**Access:** free artist project page opened

**Limits:** Historical online-image collection is described, not offered as a permissions precedent. No exact retraining recipe is provided.

Tags: video, portrait, dataset intervention, drag, StyleGAN, critical practice.

### ART13 — Wearing, Gillian: museum production account

**Gillian Wearing with Wieden + Kennedy** · 2018 work; 2021 wall text · institutional project

[Source](https://www.guggenheim.org/wp-content/uploads/2021/11/guggenheim-gillian-wearing-wearing-masks-digital-wall-text.pdf) · Evidence: opened · Process depth: partial

Medium: five-minute colour film. Wearing casts more than fifteen performers to portray her; their faces, bodies and voices are digitally combined with hers into a deepfake persona. Casting, scripting and performance remain human-authored.

**Practical use:** AI-mediated identity can be built around authored performances and a script, rather than anonymous generated footage.

**Access:** free museum PDF; relevant work entry examined

**Limits:** The relevant wall-text entry was read, not the entire 82-page PDF. The neural model and compositing pipeline are unspecified.

Tags: film, performance, deepfake, identity, museum documentation.

### ART14 — Dio: Media and Materiality

**Ben Snell; Phillips interview/account** · 2018 work; 2019 interview · firsthand interview

[Source](https://www.phillips.com/article/42361496/media-and-materiality-in-conversation-with-ben-snell) · Evidence: opened · Process depth: partial

Medium: physical sculpture. Snell trains a system with 3D models of classical sculpture, then makes its generated form from the powdered components of the computer itself. He authors training selection, fabrication and the material narrative.

**Practical use:** The output material can express the concept behind an AI process rather than simply illustrate its result.

**Access:** free interview/account opened

**Limits:** The source describes classical 3D training models and casting computer powder mixed with clear resin; architecture and a complete fabrication specification are absent. Its autonomy language is promotional.

Tags: sculpture, 3D dataset, material concept, physical output.

### ART15 — Cloud of Petals: artist conversation on collection, film and VR

**Sarah Meyohas; interview by Maisie Skidmore** · 2017 · firsthand interview

[Source](https://www.anothermag.com/art-photography/10266/the-artist-using-an-algorithm-to-generate-rose-petals) · Evidence: opened · Process depth: detailed

Medium: photography, 16mm film, a pressed-petal archive and VR. Workers photograph 100,000 petals and select favourites; Meyohas films their labour and works with ML specialists on generated petals. Human selection persists in the physical archive.

**Practical use:** Source collection, labour and subjective selection can become visible elements of the artwork.

**Access:** free artist conversation opened

**Limits:** This does not demonstrate botanical imagery suits Iana. The source documents stages but omits training parameters.

Tags: photography, archive, film, VR, data collection, human selection.

### ART16 — Not the Only One (N'TOO)

**Stephanie Dinkins** · 2018 work; 2021 model update described · artist process

[Source](https://www.stephaniedinkins.com/ntoo.html) · Evidence: opened · Process depth: detailed

Medium: voice-interactive sculpture/archive. Oral histories from three generations of Dinkins's family and culturally attuned material inform a conversational AI. The artist records, selects and aligns material, designs the entity, and iterates its model and sculptural embodiment.

**Practical use:** An authored archive may include voices and histories, with usefulness judged against the represented people's needs.

**Access:** free artist project and technical notes opened

**Limits:** Dinkins describes imperfect responses and model changes. This is an archival/social practice, not evidence for painting-style transfer.

Tags: oral history, archive, sculpture, NLP, community, small data.

### ART17 — The Call

**Holly Herndon and Mat Dryhurst; Serpentine Arts Technologies and participating choirs** · 2024–2025 · institutional project

[Source](https://www.serpentinegalleries.org/whats-on/holly-herndon-mat-dryhurst-the-call/) · Evidence: opened · Process depth: detailed

Medium: choral sound installation. A composed songbook and recording protocol guide sessions with fifteen community choirs; recordings train choral AI models. Artists, singers, researchers and designers author different stages, with contributor governance explored through a Data Trust.

**Practical use:** Design source-making and contributors' roles before treating a model as the artwork's sole author.

**Access:** free institutional project page and credits opened

**Limits:** Sound and collective governance are the transferable ideas; this is not a visual painting workflow or a checked public model service.

Tags: sound, participation, authored dataset, consent, choral AI, installation.

### ART18 — Artificial Life: a process interview

**Sofia Crespo; interview by Andrew Dubber, MTF Labs** · 2021 · firsthand interview

[Source](https://shows.acast.com/mtflabs/episodes/67ceea6dd64d9d8e86dc852e) · Evidence: opened · Process depth: detailed

Medium: synthetic-organism imagery and video. Crespo explains collecting subject-specific datasets, training separate caterpillar and butterfly models, then connecting their nearest visual states. She authors datasets, transitions and selection among many generated alternatives.

**Practical use:** Separate models or collections can provide different visual vocabularies whose relationship the artist composes.

**Access:** free podcast transcript opened; audio not auditioned

**Limits:** Organic/uncanny forms are contextual, not recommended aesthetics. The transcript was examined; no model or audio was run.

Tags: video, dataset curation, synthetic biology, GAN, organic aesthetic.

### ART19 — The Substitute

**Alexandra Daisy Ginsberg; animation by The Mill** · 2019 · artist process

[Source](https://www.daisyginsberg.com/work/the-substitute) · Evidence: opened · Process depth: partial

Medium: paired video installation. A rendered rhino's behaviour is based on DeepMind agent research; animal behaviours and sounds are adapted from research footage. Ginsberg and collaborators author the ecological premise, animation and dual-screen presentation.

**Practical use:** AI-derived behaviour can serve a specific conceptual question rather than operate as decorative movement.

**Access:** free artist project page opened

**Limits:** The artist credits animation based on research; this page does not establish a live-learning system in the gallery.

Tags: video, animation, agent research, ecology, contextual reference.

### ART20 — Feminist Data Set: toolkit and process

**Caroline Sinders** · 2020 reader; project begun 2017 · artist process

[Source](https://carolinesinders.com/wp-content/uploads/2020/05/Feminist-Data-Set-Final-Draft-2020-0526.pdf) · Evidence: opened · Process depth: detailed

Medium: participatory workshops, archive and toolkit. People define categories and submit material; Sinders reviews submissions and adjusts subsequent collection to address exclusions. The artwork examines human decisions throughout a future machine-learning pipeline.

**Practical use:** Collecting, naming, rejecting and documenting source material can be artistic work in its own right.

**Access:** free artist toolkit PDF; process and workshop sections examined

**Limits:** The reader explicitly presents a complete feminist AI as prospective. This is upstream AI-art practice, not a finished generative-image system.

Tags: archive, workshop, data curation, participation, upstream practice, critical practice.

## Books and institutions

### LIT01 — Digital Art, fourth edition

**Christiane Paul** · 2023 · book

[Source](https://thamesandhudsonusa.com/books/digital-art-softcover-fourth) · Evidence: opened · Process depth: partial

A historical and critical survey covering digital media's relationship to painting, print, photography and sculpture, alongside AI, installation and collecting.

**Practical use:** Use it to choose an artistic lineage and presentation medium before choosing software.

**Access:** Publisher metadata and description opened; sample-spread links present but not inspected; full book not retrieved.

**Limits:** Broad digital-art history, with AI as one topic; not a contemporary image-generator or painting manual. Assessment is based on the publisher description.

Tags: AI and adjacent digital art, history, theory, painting, physical output.

### LIT02 — Artificial Aesthetics: Generative AI, Art and Visual Media

**Lev Manovich and Emanuele Arielli** · 2024; collected PDF posted 2025 · book

[Source](https://manovich.net/index.php/projects/artificial-aesthetics) · Evidence: opened · Process depth: partial

Essays examine creative agency, aesthetic judgment, perception, media history and the status of AI images.

**Practical use:** Create a studio rubric separating visual appeal, personal intention, authorship and useful surprise.

**Access:** Free author-hosted 194-page complete PDF retrieved; front matter, contents and selected passages inspected; not read cover-to-cover.

**Limits:** Critical theory rather than a software manual. The author requests a 2024 citation while dating the collected PDF January 15, 2025. Not read cover-to-cover.

Tags: AI art, open access, theory, aesthetics, evaluation.

### LIT03 — The Perception Machine: Our Photographic Future between the Eye and AI

**Joanna Zylinska** · 2023 · book

[Source](https://mitpress.mit.edu/9780262546836/the-perception-machine/) · Evidence: opened · Process depth: partial

Connects computational photography and machine vision with perception and the author's photographic, collage, film and installation projects.

**Practical use:** Examine how photographic references and machine interpretation change a painting's point of view.

**Access:** Publisher metadata and OA notice opened; full-text endpoint returned 403 on 3 November 2026; no full book retrieved.

**Limits:** Theory and artistic inquiry, not a painting workflow. Open-access status is confirmed by MIT Press; the full book was not retrieved or read.

Tags: AI art, machine vision, critical theory, photography, collage.

### LIT04 — Computational Formalism: Art History and Machine Learning

**Amanda Wasielewski** · 2023 · book

[Source](https://mitpress.mit.edu/9780262545648/computational-formalism/) · Evidence: opened · Process depth: partial

Studies how artwork datasets, style categories and machine vision shape computational art-historical analysis.

**Practical use:** Question whether a model's apparent stylistic match captures the artist's decisions or merely recurring visual features.

**Access:** Publisher metadata and OA notice opened; DiVA PDF routes timed out and institutional record denied access on 3 November 2026; no book full text retrieved.

**Limits:** AI analysis of art is the central subject, rather than making paintings. Publisher description checked; full book not read.

Tags: AI and art analysis, datasets, style, critical theory, evaluation.

### LIT05 — Artificial Intelligence and the Arts: Computational Creativity, Artistic Behavior, and Tools for Creatives

**Penousal Machado, Juan Romero and Gary Greenfield, editors** · 2021 · book

[Source](https://link.springer.com/book/10.1007/978-3-030-59475-6) · Evidence: opened · Process depth: partial

Technical collection spanning visual art, music, design and games; visual-art chapters include artificial life, search-based art and neural style transfer.

**Practical use:** Ask a technical collaborator which model family fits a specific studio task instead of treating all generative systems alike.

**Access:** Publisher overview and table of contents opened; full chapters/book not retrieved.

**Limits:** Research-oriented and partly mathematical; contents were checked, not complete chapters. Predates today's image-generator interfaces.

Tags: AI art, technical reference, style transfer, evolutionary art, research.

### LIT06 — Computers and Creativity

**Jon McCormack and Mark d'Inverno, editors** · 2012 · book

[Source](https://link.springer.com/book/10.1007/978-3-642-31727-9) · Evidence: opened · Process depth: partial

Interdisciplinary collection joins computational creativity, aesthetic evaluation and artists' approaches across visual, musical and interactive work.

**Practical use:** Compare designing a system, selecting its outputs and making the final material work as different creative decisions.

**Access:** Publisher overview and table of contents opened; full chapters/book not retrieved.

**Limits:** Foundational computational-art and creativity research, including AI and evolutionary systems; not a diffusion-model guide. No full-book reading.

Tags: AI and adjacent computational art, creativity, evaluation, history, research.

### LIT07 — The Practice of Art and AI: European ARTificial Intelligence Lab

**Andreas J. Hirsch, Markus Jandl and Gerfried Stocker, editors** · 2021 · book

[Source](https://hatjecantz.de/en/collections/best-selling-collection/products/59005-the-practice-of-art-and-ai) · Evidence: opened · Process depth: partial

Documents art-and-AI projects through the European ARTificial Intelligence Lab and Ars Electronica's art/science context.

**Practical use:** Find comparable projects and collaborators, then trace an individual project's process rather than copying its appearance.

**Access:** Publisher record opened; print marked permanently out of stock. Ars Electronica advertises a free 6 MB PDF in search extraction, but the download page and PDF returned 403 on 3 November 2026; full book not retrieved.

**Limits:** Publisher record verified; catalogue contents and full book were not inspected. Do not equate an advertised archive download with successful full-text retrieval.

Tags: AI art, artist projects, institutional practice, art and science, catalogue context.

### LIT08 — Digital Art: 1960s to Now

**Pita Arreola, Corinna Gardner and Melanie Lenz** · 2024 · book

[Source](https://www.vam.ac.uk/shop/books/design-books/digital-art-1960s-to-now-169111.html) · Evidence: opened · Process depth: partial

Decade-based history combines essays with interviews involving artists, curators, gallerists and collectors, from computer works on paper to contemporary digital practice.

**Practical use:** Study how artists move between drawings, systems, installations and institutions while retaining a coherent practice.

**Access:** Museum shop metadata and description plus V&A research page opened; sample-spread links present but not inspected; full book not retrieved.

**Limits:** AI is part of a broader history. The V&A research-project page confirms the 2024 publication; the book was not read in full.

Tags: AI and adjacent digital art, history, artist interviews, works on paper, presentation.

### LIT09 — Artistes & robots

**Laurence Bertrand Dorléac and Jérôme Neutres, editors; Grand Palais Rmn** · 2018 · catalogue

[Source](https://editions.grandpalaisrmn.fr/fr/editions/EC107109?guid=6ab4fd0807724) · Evidence: opened · Process depth: showcase

Exhibition catalogue provides a route into robot-assisted and autonomous art, complemented by the institution's educational materials.

**Practical use:** Compare the role of physical gestures, autonomy and audience experience before considering robotic output.

**Access:** Publisher catalogue record opened; associated 31-page teacher dossier and 8-page English visitor guide retrieved and sampled; catalogue itself not retrieved.

**Limits:** French-language catalogue; book record rather than full text inspected. The exhibition includes rule-based and robotic work beyond machine learning.

Tags: AI and adjacent robotic art, catalogue, physical output, history, French.

### LIT10 — Generative Art: A practical guide using Processing

**Matt Pearson** · 2011 · book

[Source](https://www.manning.com/books/generative-art) · Evidence: opened · Process depth: detailed

Instructional introduction to algorithmic image making with Processing, including randomness, noise, emergence, autonomy and fractals.

**Practical use:** Build a small rule-driven study of line, spacing or rhythm as a comparison with an AI-assisted study.

**Access:** Publisher metadata and 14-page sample/contents opened; full book not retrieved; code not run.

**Limits:** Adjacent generative coding, not machine learning. Detailed steps are described by the publisher and contents; old code was not run or validated.

Tags: adjacent computational art, practical manual, creative coding, composition, Processing.

### LIT11 — Creative AI Lab: tools, resources and R&D Labyrinths

**Serpentine Galleries and King's College London; R&D Labyrinths with Trust** · 2020–ongoing; walkthrough series launched 2021 · institutional archive

[Source](https://www.serpentinegalleries.org/whats-on/creative-ai-lab/) · Evidence: opened · Process depth: partial

Research programme links tool resources, discussions and artist-led software walkthroughs. R&D Labyrinths describes step-by-step poetry, composition and governance examples.

**Practical use:** Use its walkthrough format to document source material, interface choices and artistic decisions in a painting experiment.

**Access:** Free Serpentine Lab and R&D Labyrinths descriptions and KCL project page opened; videos, database entries and tools not tested. Programme page remains labelled ongoing.

**Limits:** The three observed walkthrough descriptions concern poetry, music and collective governance, not painting recipes. Historical tool links may need fresh compatibility checks.

Tags: AI art, process documentation, tools, artist walkthroughs, cross-media.

### LIT12 — Future Art Ecosystems 4: Art x Public AI

**Serpentine Arts Technologies, drawing on Creative AI Lab research** · 2024 · institutional archive

[Source](https://www.serpentinegalleries.org/whats-on/future-art-ecosystems-4-art-x-public-ai/) · Evidence: opened · Process depth: partial

Institutional briefing examines the AI stack and cultural organisations' ability to shape AI infrastructure.

**Practical use:** Before commissioning a studio system, identify who controls data, model access, compute and continuing support.

**Access:** Volume-specific Serpentine launch page and series overview retrieved; launch dated 19 March 2024. Full briefing reader could not be retrieved on 3 November 2026; briefing not read.

**Limits:** Infrastructure and cultural policy, not visual technique. Programme and launch date checked; full report was not retrieved or read. This is the 2024 FAE4 volume, not the latest series volume; the series page now also lists FAE5.

Tags: AI art, infrastructure, institutional practice, data, strategy.

### LIT13 — European ARTificial Intelligence Lab archive

**Ars Electronica and European cultural/scientific partners** · 2018–2021 · institutional archive

[Source](https://archive.aec.at/ailab/) · Evidence: opened · Process depth: partial

Historical programme archive indexes residencies, activities, partners and juries around artistic engagement with AI.

**Practical use:** Follow a residency from artistic question to scientific partnership and exhibition, looking for viable collaboration models.

**Access:** Free archive introduction opened; dynamic results remained Loading data in text extraction; no individual residency record or current application offer verified.

**Limits:** Completed programme, not a current residency offer. The landing page does not establish process detail for every indexed project or reusable code.

Tags: AI art, residencies, archive, art and science, collaboration.

### LIT14 — Renaissance 3.0: A Base Camp for New Alliances of Art and Science in the 21st Century

**ZKM | Center for Art and Media Karlsruhe; curators Peter Weibel and Anett Holzheid** · 2023–2024 · institutional archive

[Source](https://zkm.de/en/exhibition/2023/03/renaissance-30) · Evidence: opened · Process depth: partial

Exhibition archive follows artistic laboratories and shared art/science tools, with individual works and linked interviews.

**Practical use:** Consider how a technical experiment becomes a material artwork with a subject, duration and installation context.

**Access:** Free historical exhibition page, work catalogue index and the native picture object description opened; videos/talks not played; no current workshop availability established.

**Limits:** Broad art/science and computational practice, not exclusively AI. Historical workshops listed on the page are past events; no current attendance is implied.

Tags: adjacent computational art, art and science, archive, materiality, interviews.

### LIT15 — AI: More than Human

**Barbican; curators Suzanne Livingston and Maholo Uchida** · 2019 original exhibition; touring resource · institutional archive

[Source](https://www.barbican.org.uk/hire/exhibition-touring-barbican-immersive/ai-more-than-human) · Evidence: opened · Process depth: showcase

Exhibition places artistic commissions alongside scientific AI research and questions about human-machine relationships.

**Practical use:** Use artist interviews to compare the intended experience of an artwork with the technical system producing it.

**Access:** Free touring overview and original 2019 event archive opened; interview/essay links observed but media not played. Hire availability from mid-April 2027 is institutional touring information.

**Limits:** A survey rather than a production manual. The original 2019 exhibition is past; the current touring-hire page is not a current public exhibition listing.

Tags: AI art, exhibition, artist interviews, critical context, audience experience.

### LIT16 — Chance and Control: Art in the Age of Computers

**Victoria and Albert Museum** · 2018 · institutional archive

[Source](https://www.vam.ac.uk/exhibitions/chance-and-control-art-in-the-age-of-computers) · Evidence: opened · Process depth: showcase

Displays computer-generated prints, drawings and paintings by artists including Vera Molnár, Frieder Nake, Manfred Mohr and Roman Verostko.

**Practical use:** Compare controlled variation in line and composition with a hand-painted series, using actual works on paper as references.

**Access:** Free past-display overview and artwork highlights opened; 2-page conference programme retrieved (26 October 2018); no procedural manual or current enrollment.

**Limits:** Predominantly adjacent algorithmic art, not evidence about modern learned image models. Past display and conference; no procedural reproduction instructions.

Tags: adjacent computational art, history, works on paper, composition, archive.

### LIT17 — A Shift in Artistic Practices through Artificial Intelligence

**Kıvanç Tatar, Petter Ericson, Kelsey Cotton, Paola Torres Núñez del Prado, Roser Batlle-Roca, Beatriz Cabrero-Daniel, Sara Ljungblad, Georgios Diapoulis and Jabbar Hussain** · 2024; preprint first posted 2023 · journal

[Source](https://aicomparts.com/projects/2024-leonardo/) · Evidence: opened · Process depth: partial

Leonardo article surveys how accessible AI systems challenge artistic roles, conventions and practices across media.

**Practical use:** Name which studio roles a system changes: proposing, selecting, composing, producing or performing.

**Access:** Author page and arXiv metadata opened; free 13-page author-deposited manuscript PDF retrieved and sampled. Former five-page UPF published-PDF endpoint returned 502 on 3 November 2026; publisher DOI returned 403.

**Limits:** Short field overview, not a controlled study demonstrating improved paintings or a complete production recipe. Published article and preprint dates differ.

Tags: AI art, journal, artistic practice, cross-media, open access.

### LIT18 — Creative Applications of Deep Learning with TensorFlow

**Parag Mital; Kadenze** · 2016 · course

[Source](https://www.kadenze.com/courses/creative-applications-of-deep-learning-with-tensorflow/info) · Evidence: search-only · Process depth: partial

Syllabus describes dataset preparation, network building, generative models and creative applications using an early TensorFlow stack.

**Practical use:** Use its dataset-to-model-to-experiment structure when discussing a learning plan with a technical collaborator.

**Access:** Historical Kadenze syllabus and Enrollment Closed label verified only through search extraction; direct page fetch timed out on 3 November 2026. Author-owned archived CADL README and notebook index opened; video access/enrollment and code compatibility untested.

**Limits:** Historical technical course, not a verified current class. Canonical page lists TensorFlow 0.11.0; the separate -i offering lists 0.9.0. Dataset, network, DeepDream/style-transfer and generative-model lessons are historical instruction, not physical painting technique.

Tags: AI art, archived course, technical education, datasets, historical software.

### LIT19 — CODE 2024: Deep Nudes and Digital Oblivion

**IMPAKT Centre for Media Culture and collaborating artists/partner organisations** · 2024 · institutional archive

[Source](https://impakt.nl/events/2024/exhibition/code-2024/) · Evidence: opened · Process depth: partial

Documents a collaborative art programme addressing AI images, digital identity, opaque models and control over personal data.

**Practical use:** Choose a concrete artistic question about representation or agency before building an AI intervention.

**Access:** Free exhibition archive and project list opened; individual project workflows not retrieved; physical exhibition and artist talks took place in 2024.

**Limits:** Critical media-art projects rather than painter-facing technique. A six-month co-creation process is documented, but the overview does not provide complete technical workflows.

Tags: AI art, critical practice, digital identity, collaboration, archive.

## Workflows and papers

### LAB01 — InvokeAI: Crafting images with the Canvas

**InvokeAI contributors** · Date not established · official workflow

[Source](https://v7.invoke.ai/users-guide/canvas/introduction/) · Evidence: opened · Process depth: detailed

A raster painting, mask and regional guidance become candidate edits, staged for acceptance into layers.

**Practical use:** The artist draws masks, adjusts denoising and accepts or discards results. An abstract painter could isolate one unresolved passage.

**Access:** free documentation; application/model setup not tested

**Limits:** Versioned v7 documentation; controls depend on model support. Documented masking does not establish fidelity to an individual practice.

Tags: artist-directed-editing, own-reference-style, hands-on, layers, inpainting.

### LAB02 — ComfyUI inpainting and outpainting examples

**ComfyUI project** · Date not established · official workflow

[Source](https://comfyanonymous.github.io/ComfyUI_examples/inpaint/) · Evidence: opened · Process depth: detailed

An image and alpha mask feed an editable node workflow; padding extends its bounds for outpainting.

**Practical use:** The artist chooses the editable region and inspects workflow parameters. Useful for making variations around a retained painted fragment.

**Access:** free examples with embedded workflows; checkpoints not downloaded

**Limits:** These examples name older v2/AnythingV3 checkpoints. Loading workflow metadata is documented; compatibility with a fresh installation was not tested.

Tags: artist-directed-editing, hands-on, inpainting, outpainting, embedded-workflow.

### LAB03 — Photoshop: Use reference images for consistent results

**Adobe** · 2026 · official workflow

[Source](https://helpx.adobe.com/photoshop/desktop/create-open-import-images/create-images/use-reference-images-for-consistent-results.html) · Evidence: opened · Process depth: detailed

A selection plus uploaded reference guides Generative Fill; the guide distinguishes whole-image/object references and placing/swapping content.

**Practical use:** The artist supplies both region and example. Try one approved motif as reference, then compare candidates against a manually composed study.

**Access:** free instructions; Photoshop and generation access separate

**Limits:** Commercial application and model-specific options; this manual demonstrates controls, not exact copying, style fidelity or a verified free generation entitlement.

Tags: artist-directed-editing, own-reference-style, hands-on, reference-image, commercial-tool.

### LAB04 — Draw Things Basic UI guide

**Draw Things community documentation contributors** · Date not established · creator-hosted community guide

[Source](https://github.com/drawthingsai/community-docs/blob/main/Documentation.docc/1.UI.md) · Evidence: opened · Process depth: detailed

The guide covers canvas drawing, imported images, inpainting, seeds, project history and configuration templates.

**Practical use:** The artist retains drawing, erasing, strength and seed choices. It offers a route from a rough colour sketch to saved alternatives.

**Access:** free community guide hosted by tool creator

**Limits:** Community-authored, with an explicitly old UI section. Treat historical resolutions and button locations as version-specific; application and models were not tested.

Tags: artist-directed-editing, hands-on, sketch-to-image, local-workflow, community-authored.

### LAB05 — Diffusers: Image-to-image

**Hugging Face Diffusers maintainers** · Date not established · official workflow

[Source](https://huggingface.co/docs/diffusers/using-diffusers/img2img) · Evidence: opened · Process depth: detailed

A starting image and prompt produce a transformed image; examples vary strength, guidance and model family.

**Practical use:** The artist chooses the initial block-in and change amount. A small strength sweep could reveal when useful variation becomes unwanted rewriting.

**Access:** free documentation with executable code examples; not executed

**Limits:** Python/model setup is required. Examples use specific diffusion architectures; a strength value is not a portable percentage of artistic fidelity.

Tags: artist-directed-editing, hands-on, image-to-image, parameter-study.

### LAB06 — SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations

**Chenlin Meng and colleagues** · 2021; ICLR 2022 · paper/project

[Source](https://chenlin9.github.io/SDEdit/) · Evidence: opened · Process depth: detailed

Coloured strokes or a rough composite are noised and denoised into image variants using a pretrained diffusion prior.

**Practical use:** The artist supplies the arrangement and edits; its noise-versus-retention tradeoff explains why a block-in can guide without precisely constraining output.

**Access:** open paper, project and original code; not executed

**Limits:** Original checkpoints target faces, bedrooms and churches. Realism-oriented results do not establish suitability for preserving abstract marks.

Tags: artist-directed-editing, sketch-to-image, foundational, image-to-image.

### LAB07 — IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models

**Hu Ye and colleagues; Tencent AI Lab** · 2023 · paper/project

[Source](https://github.com/tencent-ailab/IP-Adapter) · Evidence: opened · Process depth: detailed

A reference image conditions generation alongside text, without training a new adapter for each supplied image.

**Practical use:** The artist chooses references and image influence. Compare reference-guided motif or palette studies before committing to training on an archive.

**Access:** open paper and official code/notebooks; not executed

**Limits:** Adapters must match their base architecture. Original defaults center-crop references, potentially losing peripheral marks; similarity is not an authorship/style guarantee.

Tags: own-reference-style, artist-directed-editing, reference-image, adapter.

### LAB08 — DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation

**Nataniel Ruiz and colleagues; Google Research** · 2022; CVPR 2023 · paper/project

[Source](https://dreambooth.github.io/) · Evidence: opened · Process depth: detailed

A selected subject-image set fine-tunes a model, associating an identifier with that subject for new renditions.

**Practical use:** The artist authors the training set and judges retained identity. Useful background for recurring personal motifs, rather than automatic style certification.

**Access:** open original paper/project; separate Diffusers training implementation opened

**Limits:** Original work used Imagen; linked Diffusers training is a separate implementation. Few-image subject experiments do not establish a universal painting-dataset minimum.

Tags: own-reference-style, personalization, training, foundational.

### LAB09 — Training Generative Adversarial Networks with Limited Data / StyleGAN2-ADA

**Tero Karras and colleagues; NVIDIA** · 2020; PyTorch implementation 2021 · paper/project

[Source](https://github.com/NVlabs/stylegan2-ada-pytorch) · Evidence: opened · Process depth: detailed

A curated dataset trains or fine-tunes a GAN; adaptive augmentation addresses discriminator overfitting under limited data.

**Practical use:** The artist controls archive selection and sample curation. Useful for understanding dataset-shaped visual worlds and interpolation, beyond text prompting.

**Access:** open paper and official training code; not executed

**Limits:** Historical CUDA/PyTorch stack. Limited-data experiments are not evidence that five artwork photographs reliably capture an artist’s practice.

Tags: own-reference-style, training, gan, dataset-authorship.

### LAB10 — InstructPix2Pix: Learning to Follow Image Editing Instructions

**Tim Brooks, Aleksander Holynski and Alexei A. Efros** · 2022; CVPR 2023 · paper/project

[Source](https://www.instruct-pix2pix.timothybrooks.com/) · Evidence: opened · Process depth: detailed

An existing image plus an editing instruction produces an edited image without per-image fine-tuning or inversion.

**Practical use:** The artist specifies a change and rejects collateral changes. Compare a single palette/material instruction with a manually painted counterpart.

**Access:** open paper, project and official code; not executed

**Limits:** The project shows excessive edits and failures to isolate objects or reorganize scenes. Its 2023 model is a historical baseline.

Tags: artist-directed-editing, instruction-editing, foundational.

### LAB11 — DragDiffusion: Harnessing Diffusion Models for Interactive Point-based Image Editing

**Yujun Shi and colleagues** · 2023; CVPR 2024 · paper/project

[Source](https://yujun-shi.github.io/projects/dragdiffusion.html) · Evidence: opened · Process depth: detailed

An image, editable mask and handle/target points produce a spatially deformed image through latent optimization.

**Practical use:** The artist chooses where a form moves. Potentially useful for studying spacing or silhouette shifts without describing them in prose.

**Access:** open paper, project and official UI code; not executed

**Limits:** Original real-image workflow first trains an image-specific LoRA; documented setup targets NVIDIA/Linux and an older Diffusers version.

Tags: artist-directed-editing, hands-on-research, point-editing, composition.

### LAB12 — Plug-and-Play Diffusion Features for Text-Driven Image-to-Image Translation

**Narek Tumanyan, Michal Geyer, Shai Bagon and Tali Dekel** · 2022; CVPR 2023 · paper/project

[Source](https://pnp-diffusion.github.io/) · Evidence: opened · Process depth: detailed

A source image and target prompt yield a translated image, with source features injected to retain semantic layout.

**Practical use:** The artist supplies composition and chooses structural influence. Compare surface or colour alternatives while checking that key relationships survive.

**Access:** open paper, project and official code; not executed

**Limits:** Original code targets Stable Diffusion v1.4. Layout preservation can leak source appearance; it is not exact contour or brushwork retention.

Tags: artist-directed-editing, structure-control, image-to-image.

### LAB13 — Paint by Example: Exemplar-based Image Editing with Diffusion Models

**Binxin Yang and colleagues** · 2022; CVPR 2023 · paper/project

[Source](https://github.com/Fantasy-Studio/Paint-by-Example) · Evidence: opened · Process depth: detailed

A source image, region mask and exemplar image become a reference-conditioned inpainting result.

**Practical use:** The artist supplies where and what visually. An approved motif or material study can communicate changes that are difficult to describe.

**Access:** open paper and official code with inference examples; not executed

**Limits:** The model intentionally transforms exemplars rather than pasting pixels. Original checkpoints and environment require inspection; exact reference fidelity is unproven.

Tags: own-reference-style, artist-directed-editing, reference-image, inpainting.

### LAB14 — SemanticDraw: Towards Real-Time Interactive Content Creation from Image Diffusion Models

**Jaerin Lee and colleagues** · 2024; CVPR 2025 · paper/project

[Source](https://github.com/ironjr/semantic-draw) · Evidence: opened · Process depth: detailed

Hand-drawn regions receive separate semantic prompts, producing an evolving raster image through a streaming diffusion pipeline.

**Practical use:** The artist paints regions and changes their meaning. Promising for testing balances of differently described areas in a composition.

**Access:** open paper and official code with demos; not executed

**Limits:** Speed claims depend on published hardware/settings. Model-specific SD1.5, SDXL and SD3 demos are documented; arbitrary-model compatibility was not tested.

Tags: artist-directed-editing, hands-on-research, semantic-brushes, regional-control.

### LAB15 — PromptPaint: Steering Text-to-Image Generation Through Paint Medium-like Interactions

**John Joon Young Chung and Eytan Adar** · 2023 · paper/project

[Source](https://github.com/johnr0/PromptPaint) · Evidence: opened · Process depth: partial

Prompt mixtures, stencils and interventions steer different areas and stages of image generation through a paint-inspired interface.

**Practical use:** The artist mixes concepts and intervenes during generation. Valuable design precedent for gradual exploration rather than a single prompt submission.

**Access:** open author paper and code; publisher fetch returned 403

**Limits:** Research setup spans local services, Colab and ngrok, possibly paid compute. Interface studies do not establish superiority for abstract painters.

Tags: artist-directed-editing, co-drawing, interaction-design, prompt-mixing.

### LAB16 — Collaborative Neural Painting

**Nicola Dall’Asen and colleagues** · 2023; CVIU 2025 · paper/project

[Source](https://github.com/Fodark/collaborative-neural-painting) · Evidence: opened · Process depth: partial

User brushstrokes or an object class condition proposed stroke sequences, allowing iterative editing and composition.

**Practical use:** The artist can modify individual strokes during completion. Its editable representation is a useful precedent for preserving decisions beyond final raster pixels.

**Access:** open paper/project and official code; dataset release incomplete

**Limits:** Dataset remains marked Coming soon; checkpoint download is linked but untested. Object-painting research does not demonstrate an arbitrary-archive collaborator. The project page also marks the demo Coming Soon.

Tags: co-drawing, editable-strokes, artist-directed-editing, research-prototype.

### LAB17 — FRIDA: A Collaborative Robot Painter with a Differentiable, Real2Sim2Real Planning Environment

**Peter Schaldenbrand, James McCann and Jean Oh** · 2022; ICRA 2023 · paper/project

[Source](https://pschaldenbrand.github.io/frida/) · Evidence: opened · Process depth: detailed

Human text, sketch or reference goals become planned brushstrokes, physically executed and revised from camera feedback.

**Practical use:** The artist supplies goals and material context. It demonstrates a genuine canvas output and the importance of adapting to actual paint behaviour.

**Access:** open paper/project and shared official robot code; hardware not tested

**Limits:** Requires robot, camera, calibrated workspace and material setup. A simulator or open repository does not provide a ready studio assistant.

Tags: physical-output, own-reference-style, robot-painting, material-feedback.

### LAB18 — CoFRIDA: Self-Supervised Fine-Tuning for Human-Robot Co-Painting

**Peter Schaldenbrand and colleagues** · 2024 · paper/project

[Source](https://pschaldenbrand.github.io/cofrida/) · Evidence: opened · Process depth: detailed

A partially painted canvas and text goal guide new robot marks, with a model adapted to physical execution constraints.

**Practical use:** The person keeps painting and redirecting the collaboration. The project specifically documents human watercolour combined with robot marker work.

**Access:** open paper/project and shared official robot code; hardware not tested

**Limits:** Research robot integration requires calibration and compatible materials. Published mixed-media examples do not guarantee preservation of any artist’s existing marks.

Tags: physical-output, co-drawing, mixed-media, robot-painting.

### LAB19 — Diffusion Illusions: Hiding Images in Plain Sight

**Ryan Burgert and colleagues** · 2023; SIGGRAPH 2024 · paper/project

[Source](https://diffusionillusions.com/) · Evidence: opened · Process depth: detailed

Chosen prompts or images guide jointly optimized images that reveal different content when flipped, rotated or physically overlaid.

**Practical use:** The artist chooses paired readings and arrangement. Offers an edition/object route through transparencies, backlighting or hinged tiles.

**Access:** open paper/project, official notebooks and printable examples; not executed

**Limits:** Illusion constraints can dominate the imagery. Physical alignment, printing and light need trials; examples establish no compatibility with a particular painting practice. Demonstrated overlays use printed overhead sheets and backlighting; transfer to spaced hand-painted glass and coloured wall light is untested.

Tags: physical-output, mixed-media, print, optical-illusion.

### LAB20 — TokenFlow: Consistent Diffusion Features for Consistent Video Editing

**Michal Geyer, Omer Bar-Tal, Shai Bagon and Tali Dekel** · 2023; ICLR 2024 · paper/project

[Source](https://diffusion-tokenflow.github.io/) · Evidence: opened · Process depth: detailed

A source video and target prompt become an edited sequence using cross-frame feature correspondence to support consistency.

**Practical use:** The artist authors source motion and edit intent. An approved filmed brush gesture could become a controlled moving-image study.

**Access:** open paper, project and official editing code; not executed

**Limits:** Reconstruction quality and the base edit matter; authors note possible decoder jitter. Temporal coherence does not guarantee exact colour, contour or texture retention.

Tags: coherent-video, artist-directed-editing, video-to-video, temporal-consistency.

## Frameworks and context

### CTX01 — Understanding and Creating Art with AI: Review and Outlook

**Eva Cetinic and James She** · 2021 preprint; 2022 journal · survey paper

[Source](https://arxiv.org/abs/2102.09109) · Evidence: opened · Process depth: partial

Reviews both artwork analysis and new-art creation, with a bibliography spanning image collections, aesthetics and generative methods.

**Practical use:** Use its reference map to locate distinct artistic questions before choosing a model.

**Access:** open paper

**Limits:** Abstract and source record checked; not a current installation manual or proof that every cited method works on these paintings.

Tags: survey, art analysis, generative methods.

### CTX02 — Designing Creative AI Partners with COFI

**Jeba Rezwana and Mary Lou Maher** · 2022 preprint; 2023 journal · interaction research paper

[Source](https://arxiv.org/abs/2204.07666) · Evidence: opened · Process depth: partial

A framework for modelling turn-taking, contribution and communication in human–AI creative systems; the authors analyse 92 existing systems.

**Practical use:** Ask whether the artist can correct, reject, redirect and take turns with the system.

**Access:** open paper

**Limits:** Paper abstract and record checked; the framework is not a validated prediction of Iana's preferences. The authors limit the observed interaction clusters to their historical 92-system dataset.

Tags: co-creation, human control, evaluation.

### CTX03 — Painting Robot e-David — project and collaborations

**University of Konstanz Visual Computing** · Date not established · institutional process

[Source](https://www.cgmi.uni-konstanz.de/en/forschung/e-david/) · Evidence: opened · Process depth: detailed

Explains image abstraction into regions/strokes, a paint plan and camera-based feedback while a robot applies real paint. Includes collaborations with Liat Grayver.

**Practical use:** Study how material limitations, stroke planning and observation change the process of making a painting.

**Access:** Full indexed primary project text retrieved through the web reader on 3 November 2026 after an earlier restricted fetch and direct HTTP 404. A separate university collaboration article also opened. Current-origin availability remains uncertain.

**Limits:** Hardware research platform; no claim this is a downloadable turnkey studio tool. Components include AI-based semantic information and conventional control.

Tags: physical painting, robotics, feedback, artist collaboration.

### CTX04 — Wekinator examples

**Rebecca Fiebrink and contributors** · Date not established · official example repository

[Source](https://github.com/fiebrink1/wekinator_examples) · Evidence: opened · Process depth: detailed

Input/output examples and teaching examples for interactive machine learning across programming environments.

**Practical use:** A starting point for learning a relationship between an artist's gestures and a visual or sonic response.

**Access:** free code repository

**Limits:** Repository contents checked; dependencies/examples were not installed or executed. Not an image-generation painting model.

Tags: gesture, interactive machine learning, teaching, code.

### CTX05 — Machine Learning Education for Artists, Musicians, and Other Creative Practitioners

**Rebecca Fiebrink** · 2019 · education research paper

[Source](https://ualresearchonline.arts.ac.uk/id/eprint/15453/1/Fiebrink_TOCE2019_Accepted.pdf) · Evidence: opened · Process depth: detailed

Describes learning objectives, teaching strategies and evidence from courses for creative practitioners.

**Practical use:** Learn by building, demonstrating, testing and refining expressive systems, rather than beginning with model metrics alone.

**Access:** free accepted-manuscript PDF

**Limits:** Public PDF opened; historical course studies do not establish present course enrolment or current software compatibility.

Tags: education, artist learning, interactive systems.

### CTX06 — Picbreeder: A Case Study in Collaborative Evolutionary Exploration of Design Space

**Jimmy Secretan and colleagues** · 2011 · research paper

[Source](https://www.campbellssite.com/papers/secretan_ecj11.pdf) · Evidence: opened · Process depth: detailed

Documents people selecting, evolving and branching images through collaborative interactive evolution and neuroevolution.

**Practical use:** An alternative to a single prompt: let artistic preferences guide a branching search through possibilities.

**Access:** free author-hosted manuscript PDF

**Limits:** Historical research, not diffusion. The original hosted interface was not tested; an available paper does not establish a working service.

Tags: human selection, evolutionary art, collaboration, historical.

### CTX07 — Projects: Technelegy, text works and media-rich poetry

**Sasha Stiles** · Date not established · artist project archive

[Source](https://www.sashastiles.com/projects) · Evidence: opened · Process depth: partial

Documents AI co-authored poetry alongside text paintings, mixed-media objects and moving-image adaptations.

**Practical use:** See how an authored text corpus can feed a sustained practice across digital and physical publication.

**Access:** free artist project pages

**Limits:** Adjacent literary/visual practice, not an abstract-painting recipe. Some descriptions are artist statements, not reproducible training instructions.

Tags: poetry, artist archive, physical editions, moving image, adjacent.

### CTX08 — Association for Computational Creativity — publications and teaching resources

**Association for Computational Creativity** · Date not established · research discovery archive

[Source](https://computationalcreativity.net/) · Evidence: opened · Process depth: partial

A research hub linking conference proceedings, bibliographies, journals and teaching resources.

**Practical use:** Use its curated references to extend beyond a fixed list of tools or famous artists.

**Access:** free directory and proceedings links

**Limits:** A discovery portal rather than one production tutorial; homepage event text may be dated. Check individual papers and course availability.

Tags: bibliography, research archive, teaching, discovery.

## Research process and boundaries

The 31 October bibliography was compiled in specialist research lanes. All 67 records were reviewed again against primary or firsthand sources on 3 November; the audit records partial full-text access and conflicting retrieval routes. Opened describes retrieved source material, including indexed text, rather than guaranteed current-origin availability or full reading.

Seven image-generation studies were separately produced on 1 November. The user reported that Iana liked Meridian Light. This is meaningful direction feedback, not a controlled studio evaluation, material test or optical simulation. No model inference, training, purchases, artist contact, deployment or physical trials occurred during this 3 November research audit.

See [the audit, corrections, gaps and proposed experiments](../research-audit-2026-11-03/README.md). Original source records and synthesis are preserved in its before-audit snapshot.