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Poster session: ExHall D poster boards #373 - #403 at time 4pm - 6pm.
Poster board assignment: [here]
Call for Papers
Call for Papers
Workshop - Date: June 11, 2025
Location: Room: 104 E (Level 1) [Floor plan]
FGVC12 will have two paper tracks and a nectar track:
Proceedings track: 8-page papers that will appear in the official CVPR workshop proceedings
Non-archival track: 4-page extended abstracts
Nectar track: already published work
Papers in track 1 and 2 will be reviewed. They will showcase new work, along with applications of fine-grained learning. Submission will be via CMT. Please take a look at the different deadlines below.
All deadlines are set for 11:59 pm PT.
Submission via CMT: https://cmt3.research.microsoft.com/FGVC2025
1) Proceedings track:
1) Proceedings track:
The submitted papers should have 8 pages following the CVPR25 paper guidelines. These papers will be published in the official CVPR workshop proceedings. (Submissions will be given the option to be considered for the 4-page track as well if not accepted to the 8-page track. If you wish to opt into this, please submit only to the 8-page track.)
Deadline for Submission: March 05 March 07, 2025
Notification of Acceptance: March 28, 2025
Camera Ready: April 04, 2025
Submission Website: CMT-FGVC2025
In the Top Left Menu, select "FGVC2025 - CVPR Proceedings 8-pages"
2) Non-archival track:
2) Non-archival track:
Submitted papers will consist of 4-page extended abstracts, not full papers. These will not be published with the main conference, and the timeline is closer to the conference in June.
Deadline for Submission: March 31 April 02, 2025
Notification of Acceptance: May 09, 2025
Camera Ready: May 23, 2025
Submission Website: CMT-FGVC2025
In the Top Left Menu, select "FGVC2025 - Non-archival 4-pages"
3) Nectar track:
3) Nectar track:
Already published and peer-reviewed papers. It allows you to contribute to the program by presenting a paper (in the form of a poster) already published at a previous major international CV/ML conference or in a journal. This allows you to generate additional exposure for your work and network with colleagues both within and beyond the FGVC community. Submissions will not be reviewed again. Main criteria are fit of topic and the poster board availability. Please submit the link to the arxiv (or other pdf) via the CMT page below.
Deadline for Submission: April 30, 2025
Notification of Acceptance: May 23, 2025
Submission Website: CMT-FGVC2025
In the Top Left Menu, select "FGVC2025- Nectar Track"
For track 1 and 2, the authors guarantee that the submitted paper has not been previously published or accepted for publication in a substantially similar form. CVPR rules regarding plagiarism, double submission, etc., apply.
Frequently asked questions
Frequently asked questions
Q: Is the review process double blind?
A: Yes, both authors and reviewers are anonymous.
Q: What paper ID should I use in the CVPR template?
A: When you create the FGVC submission on CMT you will receive a paper ID that you can use.
Submission via CMT: Use the drop down in the top left.
Registration fee
Registration fee
Each workshop paper published in the CVPR proceedings must be registered under a full, in-person registration type (student registration is fine). Virtual registrations will not cover a paper submission.
More information: CVPR Registration
Please email fgvcworkshop@googlegroups.com with any questions.
Scope
Scope
This workshop aim to bring together researchers to explore visual recognition across the continuum between basic-level categorization and identification of individuals within a category population. Topics of interest include:
Fine-grained categorization
Novel datasets and data collection strategies
Low/few-shot learning
Self-supervised learning
Semi-supervised learning
Transfer-learning
Attribute and part-based approaches
Taxonomic prediction
Long-tailed learning
Image captioning
Image and Video generation
Out-of-distribution detection
Open-set recognition
Multi-modal learning
Using audio and video data
Using meta data e.g. geographical priors
Learning shape
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
Fine-grained applications
Product recognition
Animal biometrics and camera traps
Museum collections
Agricultural
Medical
Fashion
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