[CFP] FGVC12 -12th Workshop on Fine-Grained Visual Categorization at CVPR 2025
Nico Lang
FGVC12 - The 12th Workshop on Fine-Grained Visual Categorization
June 11/12 2025 @ CVPR 2025 in Nashville, US
Website: https://sites.google.com/view/fgvc12
Bluesky: @fgvcworkshop.bsky.social
LinkedIn: linkedin.com/company/fgvcworkshop
Email: fgvcwo...@googlegroups.com
The FGVC workshop discusses domains where expert knowledge is typically required, and investigates artificial systems that can efficiently distinguish a large number of very similar visual concepts. The scope of the workshop is broad, as fine-grained challenges appear in any computer vision sub-discipline. Hence, the relevant topics are neither restricted to vision nor categorization. Participants are encouraged to submit research papers and to take part in a set of competitions organized in conjunction with the workshop - details below. We will also have an exciting lineup of invited speakers from computer vision through to domain experts.
PAPER SUBMISSION
FGVC12 will have two paper tracks and a nectar track. 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.
All details on the submission website: https://sites.google.com/view/fgvc12/submission
1) Proceedings track: [Deadline for Submission: March 05, 2025]
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.)
2) Non-archival track: [Deadline for Submission: March 31, 2025]
Submitted papers will consist of 4-page extended abstracts, not full papers. These will not be published with the main conference.
3) Nectar track: [Deadline for Submission: April 30, 2025]
Present already published and peer-reviewed papers in the form of a poster. Main criteria are fit of topic and the poster board availability.
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.
SCOPE
The purpose of this workshop is 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 for fine-grained categorization
Low/few shot learning
Self-supervised learning
Semi-supervised learning
Transfer-learning
Attribute and part based approaches
Taxonomic prediction
Long-tailed learning
Image captioning and generation
Out-of-distribution detection
Open-set recognition
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 metadata e.g. geographical priors
Learning shape
Fine-grained applications -
Product recognition
Animal biometrics and camera traps
Museum collections
Agricultural
Medical
Fashion
COMPETITIONS
We will also be hosting several fine-grained computer vision challenges covering a range of fine-grained tasks. Most of the competitions will be hosted on Kaggle and will be announced on our website soon.
ORGANIZERS
Nico Lang (University of Copenhagen)
Elijah Cole (Altos Labs)
Suzanne Stathatos (Caltech)
Lukáš Picek (INRIA Montpellier)
Klára Janoušková (Czech Technical University in Prague)
Christine Kaeser-Chen (Google DeepMind)
Justin Kay (MIT)
Joakim Bruslund Haurum (AAU)
Xiangteng He (Peking University)
Mehmet Aygün (University of Edinburgh)
Serge Belongie (University of Copenhagen)
Oisin Mac Aodha (University of Edinburgh)
Subhransu Maji (UMass Amherst)
Sara Beery (MIT)
Grant Van Horn (UMass Amherst)