Visual Art, Generative AI, and the Legal/Ethical Dilemma Workshop @ WACV 2026

intro image here — A stylized version of the WACV 2026 image

About

Generative AI has transformed how visual art is created and circulated. Text-to-image generation systems such as Stable Diffusion, DALL·E, and Midjourney can instantly produce artworks inspired by centuries of human creativity. While these technologies democratize access to artistic tools, they also raise urgent questions about copyright, artistic integrity, and provenance. Recent controversies underscore the dilemma:

• In 2023, artists filed lawsuits alleging that diffusion models trained on datasets like LAION-5B infringed their copyrights by replicating distinctive styles without consent.

• High-profile controversies have emerged around “style mimicry,” where AI systems can reproduce the brushwork and palette of living artists—prompting protests under hashtags like #ProtectArtists.

• Legal uncertainty persists in landmark U.S. cases (e.g., Andersen v. Stability AI) and in international contexts, where courts debate whether AI-generated art constitutes a derivative work or violates the substantial similarity test.

• Questions of authorship, provenance, and authenticity now intersect with computer vision and forensics—how do we trace whether a generated work contains identifiable fragments of training data?

This workshop will bring together researchers, artists, legal scholars, and industry practitioners to critically examine the technical, legal, and societal challenges of visual art in the age of generative AI. By hosting this dialogue at WACV, we seek to bridge the computer vision community with the creative and legal domains, and to set a research agenda that safeguards artistic integrity while enabling innovation.

Call for Papers

We solicit papers in areas including (but not limited to):

• Dataset Auditing and Bias Discovery - Detecting unauthorized use of artworks in training data and evaluating them for demographic or cultural biases.

• Style Mimicry and Protection - Metrics for measuring “style similarity” and identity leakage and technical defenses against unauthorized style transfer

• Forensics and Provenance - Watermarking, fingerprinting, and AI-based methods for tracing generated images back to training samples

• Legal and Ethical Dimensions - Copyright, derivative works, and substantial similarity tests for AI art in international frameworks, moral rights, creative misuse, and artist attribution

• Human–AI Collaboration - Human–AI co-creativity in visual art and user perception studies: authenticity, trust, and cultural reception

• Societal and Policy Impact - Implications for creative industries, museums, and digital marketplaces; Responsible licensing, compensation models, and collective rights management

Submissions can include short papers (up to 4 pages including references) or full papers (up to 8 pages excluding references) in the WACV main conference format. Accepted full papers will be included in the WACV proceedings. When deciding whether a submission should be a short paper or a full paper, please consider the significance and novelty of the contributions. If the proposed approach is well-developed with sufficient theoretical and/or empirical justification, consider submitting a full paper. If the work is a simple extension or summary of published work in other venues or is in the proof-of-concept stage, a short paper will provide a good basis for discussion and feedback. We welcome papers that propose a new technical approach for any of the above, or claim to take a position regarding challenging and open-ended questions at the intersection of AI and Ethics in the Visual Art domain.