Second Workshop on Foundation Models

Paper submission:

We invite submissions on any aspect of foundation models. This includes, but is not  limited to:

     • Multi-modality foundation model
     • Model design of foundation model
     • The conflict between multi tasks of foundation model
     • Training strategy of foundation model
     • The deployment of foundation model
     • Reproducibility of foundation model
     • Resource constrained foundation model
     • Automatic data augmentation and hyperparameter optimization of foundation model
     • Unsupervised learning, domain transfer and life-long learning of foundation model
     • Computer vision datasets and benchmarks for foundation model
Performance of downstream tasks of foundation model                                                                      
     • Probabilistic based foundation model
     • Search space design of foundation model

Important Dates

Archival submissions: The proceedings of  papers accepted for archival submissions  will be published in CVPR workshop proceedings.    
    • Paper Submission Deadline: Mar 20th, 2024 (11:59 p.m. PST)
    • Notification to Authors: April 3th, 2024 (11:59 p.m. PST)
    • Camera-ready Paper Deadline: April 13th, 2024 (11:59 p.m. PST)

    • Submission Guidelines: The submissions should follow the same policy as the main conference
    • Paper formatting: Papers are limited to eight pages, including figures and tables, in the CVPR style. 
       Additional pages containing only cited references are allowed. Please download the CVPR 2024 Author Kit
       for detailed formatting instructions. Papers that are not properly anonymized, or do not use the template, or 
       have more than eight pages (excluding references) will be rejected without review.
    • Paper submission Link:
    • Review process: Double-blind (i.e., submissions need to be anonymized)
    • Supplementary Materials: Authors can optionally submit supplemental materials for the paper via CMT. 

  • Non-Archival submissions: These papers will not be incldued in the CVPR workshop   proceedings. Selected non-archival papers 
  • will be given an opportunity to present their paper to the workshop participants in oral/poster format. 

  • • For non-archival submissions, we accept:

  •     a) Short papers: Submit 4 pages of new ideas and extended abstracts. Additional pages containing only cited references are allowed.
  •     b) Previously published papers in top venues: Submit final draft of accepted/pubished papers for this category along with the
  •          complete peer-review received from the conference attached to the paper as Appendix, after references
  •     c) Re-submissions of papers rejected from CVPR 2024 main conference or similar top venues along with the complete peer-review 
  •          received from the conference attached to the paper as Appendix, after references.

  •  Paper Submission Deadline: April 18th, 2024 (11:59 p.m. PST)
    • Notification to Authors: April 26, 2024 (11:59 p.m. PST)

Accepted papers on CVPR 2023 foundation model workshop:

Accepted proceedings papers:

Winner solutions:
■    First Place Solution of Track 1                          
Weiwei Zhou*, Chengkun Ling*, Jiada Lu*, Xiaoyun Gong, Lina Cao, Weifeng Wang [PDF]                         
■    Second Place Solution of Track 1                              
Zelun Zhang*, Xue Pan [PDF]                                         
■    Third Place Solution of Track 1                                        
Yantian Wang, Defang Zhao [PDF
■    First Place Solution of Track 2
Haonan Xu, Yurui Huang, Sishun Pan, Zhihao Guan, Yi Xu *, and Yang Yang * [PDF]                               
■    Second Place Solution of Track 2
Zhenghai He* Fuzhi Duan* Jun Lin Yanxun Yu Yayun Wang Zhongbin Niu Xingmeng Hao Youxian Zheng Zhijiang Du [PDF]
■   Third Place Solution of Track 2
Jing Wang, Shuai Feng, Kaiqi Chen, Liqun Bai [PDF]                                                                                                                

Accepted extended abstracts paper: 
■   Enriching Visual Features via Text-driven Manifold Augmentation
 Moon Ye-Bin, Jisoo Kim, Hongyeob Kim, Kilho Son, Tae-Hyun Oh [PDF]
■   Self-Enhancement Improves Text-Image Retrieval in Foundation Visual-Language Models
Yuguang Yang, Yiming Wang, Shupeng Geng, Runqi Wang, Yimi Wang, Sheng Wu, Baochang Zhang* [PDF]  
■   Enhancing Comprehension and Perception in Traffic Scenarios via Task Decoupling and Large Models                                     Xiaolong Huang, Qiankun Li*  [PDF]