Computer vision has been rapidly transformed by advancements in generative models, particularly in text-to-image generation with models like Imagen 3, Stable Diffusion 3, Flux, and DALLE-3, as well as text-to-video models such as Sora, Stable Video Diffusion, and Meta MovieGen. In the realm of 3D generation, models like Zero-123, Instant 3D, and the Large Reconstruction Model (LRM) have pushed the boundaries of 3D content creation. These innovations have enabled the development of highly realistic and diverse synthetic visual datasets, complete with annotations and rich variations, which are invaluable for training and evaluating algorithms in object detection, segmentation, representation learning, and scene understanding. The second SyntaGen Workshop aims to foster collaboration and knowledge exchange across the field, bringing together experts and practitioners to propel the development of generative models and synthetic visual datasets to new heights. Through talks, paper presentations, poster sessions, and panel discussions, the workshop will catalyze breakthroughs at the intersection of generative models and computer vision applications.

Speakers

Varun Jampani
VP Research
Stability AI		 Nathan Carr
Adobe Fellow
Adobe Research		 Jia-Bin Huang
Associate Professor
University of Maryland College Park		 Sergey Tulyakov
Director of Research
Snap Inc.		 Shobhita Sundaram
MIT

Schedule

  • TBD

Accepted Papers

  • TBD

Call for Papers

We invite papers to propel the development of generative models and/or the use of their synthetic visual datasets for training and evaluating computer vision models. Accepted papers will be presented in the poster session in our workshop. We welcome submissions along two tracks:

  • Full papers: Up to 8 pages, excluding references, with option for inclusion in the proceedings.
  • Short papers: Up to 4 pages, excluding references, not for the proceedings.

Only full papers will be considered for the Best Paper award. Additionally, we offer a Best Paper and a Best Paper Runner-up award with oral presentations. All accepted papers without inclusion in the proceedings are non-archival.

Topics

The main objective of the SyntaGen workshop is to offer a space for researchers, practitioners, and enthusiasts to investigate, converse, and cooperate on the development, use, and potential uses of synthetic visual datasets made from generative models. The workshop will cover various topics, including but not restricted to:

  • Leveraging pre-trained generative models to generate data and annotations for perception-driven tasks, including image classification, representation learning, object detection, semantic and instance segmentation, relationship detection, action recognition, object tracking, and 3D shape reconstruction and recognition.
  • Extending the generative capacity of large-scale pre-trained text-to-image models to other domains, such as videos, 3D, and 4D spaces.
  • Exploring new research directions in generative models, including GANs, VAEs, diffusion models, and autoregressive models, to advance visual content generation.
  • Synergizing expansive synthetic datasets with minimally annotated real datasets to enhance model performance across scenarios including unsupervised, semi-supervised, weakly-supervised, and zero-shot/few-shot learning.
  • Enhancing data quality and improving synthesis methodologies in the context of pre-trained text-to-image (T2I), text-to-video (T2V), text-to-3D, and text-to-4D models.
  • Evaluating the quality and effectiveness of the generated datasets, particularly on metrics, challenges, and open problems related to benchmarking synthetic visual datasets.
  • Ethical implications of using synthetic annotated data, strategies for mitigating biases, verifying and protecting generated visual contents, and ensuring responsible data generation and annotation practices.

Submisison Instructions

Submissions should be anonymized and formatted using the CVPR 2025 template and uploaded as a single PDF.

Notes for registering a new OpenReview account

  • New profiles created without an institutional email will go through a moderation process that can take up to two weeks.
  • New profiles created with an institutional email will be activated automatically.

Supplemental Material

Supplemental materials optionally can be submitted along the paper manuscript on the submission deadline. They must be anonymized and uploaded either as a single PDF or a ZIP file.

Openreview submission link

Important workshop dates

  • Submission deadline: March 22nd, 11:59 PM PST
  • Decision Release: April 3rd, 11:59 PM PST
  • Camera Ready: April 7th, 11:59 PM PST (Included in Proceedings) or April 14th, 11:59 PM PST (Not included in Proceedings)
  • Workshop date: Jun 11th or 12th

Organizers

Khoi Nguyen
VinAI Research, Vietnam		 Anh Tuan Tran
VinAI Research, Vietnam		 Binh Son Hua
Trinity College Dublin, Ireland		 Supasorn Suwajanakorn
VISTEC, Thailand		 Yi Zhou
Adobe

Organizers affiliations