P13N: Personalization in Generative AI Workshop

CVPR 2026

June 2026, (half-day) in TBD

Workshop Overview

The P13N: Personalization in Generative AI workshop aims to unite researchers, practitioners, and artists from academia and industry to explore the challenges and opportunities in personalized generative systems.

Generative AI has revolutionized creativity and problem-solving across domains, yet personalization remains one of the most challenging and underexplored frontiers. Building systems that understand and adapt to individual users’ preferences, identities, or contexts raises profound technical, ethical, and societal questions. Through invited talks, panel discussions, poster sessions, and hands-on challenges, P13N serves as a platform to foster new directions in model design, evaluation, and governance for personalized generative systems.

Call for Papers is Open!

We invite submissions on all aspects of personalization in generative AI. Both short papers (4 pages, non-archival) and long papers (8 pages, archival) are welcome and should be double-blind. References do not count toward the page limits. Including supplementary material is allowed after the references.

Topics:

Advanced optimization methods for personalizing generative models
Multi-subject composition: handling multiple entities in a single scene
Cross-modal personalization: bridging text, images, video, and 3D
AR/VR personalization for handling immersive experiences
Dataset curation for benchmarking personalized generative models
Benchmark and evaluation metrics for personalization quality, style consistency, and identity preservation
New methods for personalized video generation
Ethical and privacy considerations (user consent, data ownership, transparency)
Personalized storytelling and narrative visualization
Style adaptation for digital art and illustration
Emerging applications in gaming, e-commerce, and digital marketing
Adapting LLM-based personalization approaches to vision tasks
Personalization on edge devices

Submit Your Paper

Important Dates

Description	Date	Countdown (AoE)
Submissions Open	March 1, 2026
Long-paper Deadline (archival)	March 23, 2026 23:59 AoE
Long-paper Notification	March 25, 2026 23:59 AoE
Long-paper Camera Ready	April 8, 2026 23:59 AoE
Short-paper Deadline (non-archival)	April 20, 2026 23:59 AoE
Short-paper Notification	April 25, 2026 23:59 AoE

Invited Speakers

Nataniel Ruiz is a Research Scientist at Google Deepmind and the lead author of DreamBooth, which was selected for a Best Paper Award at CVPR 2023. His main research interests revolve around generative models, and he has authored other works in the areas of controllability and personalization of diffusion models, including StyleDrop, ZipLoRA, and HyperDreamBooth.

Kfir Aberman is a founding member of Decart AI, leading the innovation in real-time, interactive generative video models. Previously, as Principal Research Scientist at Snap Research, he led the company’s Personalized Generative AI effort. His research, including breakthroughs like DreamBooth and Prompt-to-Prompt, has become foundational to how people and creators today interact with generative AI.

Tali Dekel (Tentative) is an Associate Professor at the Weizmann Institute of Science, and a Staff Research Scientist at Google DeepMind. Her groundbreaking work in video personalization and generation includes Still-Moving, TokenFlow, and Lumiere.

Or Patashnik is an assistant professor at Tel Aviv University. Her research lies at the intersection of computer graphics, computer vision, and machine learning, with a focus on generative models. She works on image and video generation, semantic editing, and personalization, driven by the goal of making visual content creation more controllable and expressive.

Schedule

9:00–9:10	Opening remarks
9:10–9:40	Invited talk 1
9:40–10:10	Invited talk 2
10:10–10:20	Coffee Break
10:20–10:50	Invited talk 3
10:50–11:20	Invited talk 4
11:20–12:30	Panel
12:30–13:30	Closing Remarks