GAIP 2026 - Generative AI for Photography

About GAIP 2026

With the rapid breakthrough of Generative AI tools, it is timely and important to provide a platform to explore both the opportunities and challenges of these technologies. Our workshop on Generative AI for Photography brings together two rapidly evolving fields: cutting-edge AI and the creative art of visual storytelling. Generative AI tools are transforming how images can be created, enhanced, and manipulated, offering photographers new possibilities for creativity, efficiency, and accessibility. At the same time, they raise critical questions about authorship, authenticity, and ethical use. To tackle these challenges, researchers from both academia and industry must collaborate and make progress in relevant research and applied technologies. The organizing committee and keynote speakers of GAIP 2026 consist of experts from both academia and industry with rich experiences in designing and developing robust Generative AI tools and transferring them to real-world solutions. GAIP 2026 provides a focused venue to discuss and disseminate research related to Generative AI for photography, helping participants understand how AI can augment traditional practices, inspire new forms of expression, and shape the future of photography.

Where

JW Marriott Starpass, Tucson, AZ, USA

(Please see Venue for directions)

When

March 6 - 7, 2026

Keynote Speakers

[More info about the keynote speakers will be updated here]

Vishal Patel

Johns Hopkins University

Xi Wang

Ecole Polytechnique, IP Paris

Xuaner Zhang

Phota Labs

GAIP 2026 Schedule

[in Tucson local time]

[More info about the schedule will be updated here]

Submission

Submission Instructions

We welcome the following three tracks of paper submissions:

Archival track (unpublished original work; up to 8 pages, excluding references and appendix)
Non-archival track (unpublished original work; 4-8 pages, excluding references and appendix)
Non-archival track (previously published work; 4-8 pages, excluding references and appendix)

For the previously published works submitted to the non-archival track, they will not undergo additional review and will only be screened for relevance to the workshop by the organizers and program committee. The authors of these submissions must specify the venue where it is accepted/published and provide the proof of acceptance in the submission form on CMT. For all the submissions, please submit at the following CMT website: GAIP 2026 CMT submission website.

The paper submissions must be in pdf format and use the WACV 2026 official templates. All submissions must be anonymous (except the published works for non-archival track) and conform to the WACV 2026 standards for double-blind review. The accepted papers of the archival track will be included in the WACV 2026 official proceedings. At least one author of each accepted submission must present the paper at the workshop in person. According to the WACV 2026 call for workshops: "All workshop presenters must participate in person. Virtual workshops or remote presentations will not be accommodated." The papers which cannot satisfy the aforesaid requirement will be removed from the GAIP workshop program.

Submission deadline: After November 6, 2025 (AoE time) (TBD)
Notification to authors: After November 20, 2025 (AoE time) (TBD)
Camera ready deadline: After November 27, 2025 (AoE time) (TBD)

We invite the submission of original and high-quality research papers in the topics related to generative AI for photography. Accepted work will be presented as either an oral, spotlight, or poster presentation. By submitting a paper to the GAIP 2026 workshop for review, the authors must agree that they are willing and able to serve as the reviewers of the GAIP 2026 workshop submissions if needed (decided by the GAIP 2026 workshop organizing team); otherwise, their submissions are subject to desk rejection.

Topics

The topics for GAIP 2026 include, but are not limited to:

Visual generation and modification for photography and cinematography.
Visual generation and modification with camera control or trajectory.
Generative AI research related to photography, cinematography, and camera, including but not limited to panorama, fisheye, perspective, film effect, and other related topics.
Multi-modal large language model for photography and cinematography.
Performance characterization of AI algorithms and systems for photography and cinematography.
Continuous refinement of AI models using active/online learning for photography and cinematography.
Limitation of current AI models for photography and cinematography.
Brave new ideas to learn AI models for photography and cinematography.