Accepted Papers
Accepted extended abstracts for FGVC10 can be accessed below.
Recognition of Unseen Bird Species by Learning from Field Guides
Andrés C. Rodríguez (ETH Zurich), Stefano D'Aronco (ETH Zurich), Rodrigo Caye Daudt (ETH Zurich), Jan D. Wegner (ETH Zurich, University of Zurich), Konrad Schindler (ETH Zurich)
[PDF]
MEID: Mixture-of-Experts with Internal Distillation for Long-Tailed Video Recognition
Xinjie Li (Pennsylvania State University), Huijuan Xu (Pennsylvania State University)
[PDF]
Fine-Grained Product Classification on Leaflet Advertisements
Daniel Ladwig (Offenburg University), Bianca Lamm (Offenburg University, Markant Services International GmbH), Janis Keuper (Offenburg University)
[PDF]
Hypergraph Propagation and Community Selection for Instant-level retrieval
Guoyuan An (KAIST), Sung Eui Yoon (KAIST)
[PDF]
METEOR: Meta-learning connecting Earth problems observed from space
Marc Russwurm (EPFL), Ribana Roscher (Forschungszentrum Jülich), Benjamin Kellenberger (Yale University), Sherrie Wang (MIT), Devis Tuia (EPFL)
[PDF]
Improving Deep Metric Learning via Discrete Representation Bottleneck
Pingchuan Ma (LMU Munich, IWR Heidelberg, MCML), Timo Milbich (LMU Munich, IWR Heidelberg, MCML), Dmytro Kotovenko (LMU Munich, IWR Heidelberg, MCML), Björn Ommer (LMU Munich, IWR Heidelberg, MCML)
[PDF]
Test-Time Amendment with a Coarse Classifier for Fine-Grained Classification
Kanishk Jain (KCIS), Shyamgopal Karthik (University of Tubingen), Vineet Gandhi (KCIS)
Training on Web Images for Surveillance Applications: Cross-Domain Fine-Grained Vehicle Classification in a Supervised Partially Zero-Shot Setting
Stefan Wolf (Karlsruhe Institute of Technology, Fraunhofer IOSB), Jurgen Beyerer (Fraunhofer Center for Machine Learning, Fraunhofer IOSB, Karlsruhe Institute of Technology)
[PDF]
Multi-Modal Dual-Tower Architectures for Entity Retrieval from Image and Text
Imad Eddine Toubal (University of Missouri), Yi-Ting Chen (Google Research), Krishnamurthy Viswanathan (Google Research), Daniel Salz (Google Research), Ye Xia (Google Research), Zhongli Ding (Google Research)
StarCraftImage: A Dataset For Prototyping Fine-Grained Multi-Agent Categorization Methods
Sean Kulinski (Purdue University), Nicholas R. Waytowich (ARL), James Z. Hare (ARL), David I. Inouye (Purdue University)
[PDF]
INVITED PAPERS
Coreset Sampling from Open-Set for Fine-Grained Self-Supervised Learning
Sungnyun Kim, Sangmin Bae, Se-Young Yun (KAIST)
[PDF]
Learning Common Rationale to Improve Self-Supervised Representation for Fine-Grained Visual Recognition Problems
Yangyang Shu, Anton van den Hengel, Lingqiao Liu (The University of Adelaide)
[PDF]
COMPETITION PAPERS
The FathomNet2023 Competition Dataset
Eric Orenstein, Kevin Barnard, Lonny Lundsten, Geneviève Patterson, Benjamin Woodward, Kakani Katija (MBARI)
[arxiv]