The 3rd CVPR Workshop on Vision Datasets Understanding

Overview

Data is the fuel of computer vision, on which state-of-the-art systems are built. A robust object detection system not only needs a strong model architecture and learning algorithms but also relies on a comprehensive large-scale training set. Despite the pivotal significance of datasets, existing research in computer vision is usually algorithm centric. Comparing the number of algorithm-centric works in domain adaptation, the quantitative understanding of the domain gap is much more limited. As a result, there are currently few investigations into the representations of datasets, while in contrast, an abundance of literature concerns ways to represent images or videos, essential elements in datasets. 

The 3rd VDU workshop aims to bring together research works and discussions focusing on analyzing vision datasets, as opposed to the commonly seen algorithm-centric counterparts. Specifically, the following topics are of interest in this workshop. 

In summary, the questions related to the proposed workshop include but are not limited to:

Important Dates for the Workshop

Note: The above deadlines apply to those who want to have their papers included in the proceedings. If you prefer not to be included into the proceedings but still want to share your work with the community, please contact the organizing committee to find out possible solutions. 

DataCV Challenge 2024

In 2024, the DataCV Challenge aims to search for an effective training set from a large-scale data pool such that a competitive target-specific model can be obtained. 

Challenge website: https://sites.google.com/view/vdu-cvpr24/competition

Important Dates for DataCV Challenge 2024

Note:  If your team would like to compete for an award (1st place, 2nd place etc), it is mandatory to submit a paper to the workshop and release the code publicly. More details are provided on the DataCV Challenge website 

Invited Speakers: 

Stephen Gould

Australian National University

Nuno Vasconcelos

University of California San Diego

Paper Submission


To ensure the high quality of the accepted papers, all submissions will be evaluated by research and industry experts from the corresponding fields. Reviewing will be double-blind and we will accept submissions on work that is not published, currently under review, and already published. All accepted workshop papers will be published in the CVPR 2024 Workshop Proceedings by Computer Vision Foundation Open Access. The authors of all accepted papers (oral/spotlight/posters) will be invited to present their work during the actual workshop event at CVPR 2024. 


Paper submission has to be in English, in pdf format, and at most 8 pages (excluding references) in double column. The paper format must follow the same guidelines as for all CVPR 2024 submissions. The author kit provides a LaTeX2e template for paper submissions. Please refer to this kit for detailed formatting instructions.


Submission Website: https://cmt3.research.microsoft.com/VDU2024


For information about whether the workshop will be in-person only, please visit the CVPR 2024 website for more attending details. 

Contact Us

For additional information please contact us.

Organizers

Fatemeh Saleh

Microsoft, Cambridge, UK

Liang Zheng

Australian National University

Qiang Qiu

Purdue University

José Lezama

Google Research

Xin Zhao

University of Science and Technology Beijing

Piotr Koniusz

Data61/ CSIRO, Australia

Qiuhong Ke

Monash University

Yue Yao

Australian National University

Ruining Yang

Northeastern University

Jiajun Ding

Narrabundah College

Program Committee

Previous UDA Workshops