FGVC7
The Seventh Workshop on Fine-Grained Visual Categorization
June 19th 2020
Organized in conjunction with CVPR 2020
Call for Papers
Deadline for Submission - 3rd April 2020 23:59 Pacific Standard Time https://cmt3.research.microsoft.com/FGVC2020/
Notification of Acceptance - late April 2020
Camera Ready - early May 2020
Scope
The purpose of this workshop is to bring together researchers to explore visual recognition across the continuum between basic level categorization (object recognition) and identification of individuals within a category population. Topics of interest include:
Fine-grained categorization
- Novel datasets and data collection strategies for fine-grained categorization
- Appropriate error metrics for fine-grained categorization
- Low shot learning
- Self-supervised learning
- Semi-supervised learning
- Transfer-learning from known to novel subcategories
- Attribute and part based approaches
- Taxonomic predictions
Human-in-the-loop
- Fine-grained categorization with humans in the loop
- Embedding human experts’ knowledge into computational models
- Machine teaching
- Interpretable fine-grained models
Multi-modal learning
- Using audio and video data
- Using geographical priors
- Learning shape
Fine-grained applications
- Product recognition
- Animal biometrics and camera traps
Submission and Reviews
We invite submission of 3 page (excluding references) extended abstracts (using the CVPR 2020 format) describing work in the domains suggested above or in closely-related areas. Accepted submissions will be presented as posters at the workshop (or online depending on decisions made by CVPR organizers). Reviewing of abstract submissions will be double-blind. The purpose of this workshop is not as a venue for publication, so much as a place to gather together those in the community working on or interested in FGVC. Submissions of work which has been previously published, including papers accepted to the main CVPR 2020 conference are allowed.
Submission of Previously Published Work
We invite submissions of relevant work which has been previously published, including papers accepted to the main CVPR 2020 conference. The purpose of the workshop is not a venue for publication, so much as a place to gather together those in the community either working on or interested in fine-grained categorization. In the case of previously published work, it is not necessary for the authors to maintain anonymity. Instead, please cite the existing publication in the submitted abstract. These will be reviewed single-blind (much as a journal is reviewed: authors are known to reviewers, reviewers unknown to authors).