Workshop location: Summit 347-348
Poster session location: Arch Building Exhibit Hall
Transformers have recently emerged as promising and versatile deep neural architecture in various domains. Since the introduction of Vision Transformers (ViT) in 2020, the vision community has witnessed an explosion of transformer-based computer vision models with applications ranging from image classification to dense prediction (e.g., object detection, segmentation), video, self-supervised learning, 3D and multi-modal learning. This workshop presents a timely opportunity to bring together researchers across computer vision and machine learning communities to discuss the opportunities and open challenges in designing transformer models for vision tasks.
Meta AI
Tel Aviv University
UC Berkeley
UC San Diego
Stanford University
Tel Aviv University
UC San Diego
Meta AI
OpenAI
DeepMind
We accept abstract submissions to our workshop. All submissions shall have maximally 4 pages (excluding references) following the CVPR 2024 author guidelines.
Submission Deadline: April 15th, 2024 (11:59pm PST)
Notification of Acceptance: May 25th, 2024
Camera-Ready Submission Deadline: June 14th, 2024
Workshop Date: June 18th, 2024
Chien-Yi Wang (NVIDIA)
Guilin Liu (NVIDIA)
Haotian Zhang (Apple AI/ML)
Jiaqi Ding (UNC-CH)
Le An (NVIDIA)
Max Gonzalez Saez-Diez (Princeton)
Fuxiao Liu (UMD)
Maying Shen (NVIDIA)
Mingyu Ding (UC Berkeley)
Min-Hung Chen (NVIDIA)
Nadine Chang (NVIDIA)
Nishant Rai (Stanford)
Shoubin Yu (UNC-CH)
Subhashree Radhakrishnan (NVIDIA)
Xizi Wang (Indiana Univ.)
Xu Ma (Northeastern Univ.)
Yi-Lin Sung (UNC-CH)
Yimu Wang (University of Waterloo)
Yunhao Gou (HKUST)
Ziwei Zhao (Indiana University)
Ziyang Wang (UNC-CH)