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3rd Workshop on Generative Models for Computer Vision

CVPR 2025


TBD Music City Center, Nashville, Tennessee

Overview

Recent advances in generative modeling leveraging generative adversarial networks, auto-regressive models, neural fields and diffusion models have enabled the synthesis of near photorealistic images, drastically increasing the visibility and popularity of generative modeling across the computer vision research community. However, these impressive advances in generative modeling have not yet found wide adoption in computer vision for visual recognition tasks. In this workshop, we aim to bring together researchers from the fields of image synthesis and computer vision to facilitate discussions and progress at the intersection of those two subfields. We investigate the question: "How can visual recognition benefit from the advances in generative image modeling?". We invite a diverse set of experts to discuss their recent research results and future directions for generative modeling and computer vision, with a particular focus on the intersection between image synthesis and visual recognition. We hope this workshop will lay the foundation for future development of generative models for computer vision tasks.

Invited Speakers

Rana Hanocka

University of Chicago

Jiatao Gu

Apple & UPenn

Zhuowen Tu

UCSD

Yiyi Liao

Zhejiang University

Covered Topics

    Submission site: OpenReview
    Author kit: CVPR Author KIT.
    We invite submissions of short papers (4 page abstracts). Accepted submissions will be presented as posters at the workshop and selected papers will be presented as spotlights. The short papers will Not be included in the proceedings of CVPR.
    Potential topics include but are not limited to:
  • Advances in generative image models
  • Inversion of generative image models
  • Training computer vision with realistic synthetic images
  • Benchmarking computer vision with generative models
  • Analysis-by-synthesis / render-and-compare approaches for visual recognition
  • Self-supervised learning with generative models
  • Adversarial attacks and defenses with generative models
  • Out-of-distribution generalization and detection with generative models
  • Ethical considerations in generative modeling, dataset and model biases

Important Dates

Event Date (Anywhere on Earth)
Workshop paper submission deadline April 25, 2025 March 25, 2025
Decisions April 30, 2025

Organizers

Adam Kortylewski
Adam Kortylewski

MPI-INF & Uni of Freiburg

Fangneng Zhan
Fangneng Zhan

Harvard University & MIT

Tian Han
Tian Han

Stevens Institute of Technology








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