Research map / Label-efficient and robust learning / Recognition and long-tail
Discrimination-Aware Mechanism for Fine-Grained Representation Learning
Check your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Apply DAM to both SCE and TriHard | SCE+TriHard · CUB-200-2011 | Recall@1: 71.2 -> 72.3 | Helped |
| Apply DAM to both SCE and TriHard | SCE+TriHard · Cars196 | Recall@1: 88.5 -> 88.9 | Helped |
| Apply DAM to both SCE and TriHard | SCE+TriHard · Market-1501 | mAP: 87.8 -> 88.9 | Helped |
| Apply DAM to both SCE and TriHard | SCE+TriHard · MSMT17 | mAP: 56.1 -> 61.6 | Helped |
| Apply DAM to SCE only (ablation) | SCE · CUB-200-2011 | Recall@1: 69.8 -> 70.9 | Helped |
| Apply DAM to TriHard only (ablation) | SCE+TriHard · CUB-200-2011 | Recall@1: 71.2 -> 71.9 | Helped |
| Apply DAM to SCE only (ablation) | SCE · Cars196 | Recall@1: 86.9 -> 88.1 | Helped |
| Apply DAM to TriHard only (ablation) | SCE+TriHard · Cars196 | Recall@1: 88.5 -> 88.6 | Helped |
| Apply DAM to SCE only (ablation) | SCE · Market-1501 | mAP: 85.8 -> 86.7 | Helped |
| Apply DAM to TriHard only (ablation) | SCE+TriHard · Market-1501 | mAP: 87.8 -> 88.1 | Helped |
| Apply DAM to SCE only (ablation) | SCE · MSMT17 | mAP: 48.6 -> 53.2 | Helped |
| Apply DAM to TriHard only (ablation) | SCE+TriHard · MSMT17 | mAP: 56.1 -> 60.2 | Helped |
Closest papers by meaning
- Fine-Grained Recognition: Accounting for Subtle Differences between Similar Classes (AAAI 2020 · similarity 0.90)
- Twofold Debiasing Enhances Fine-Grained Learning with Coarse Labels (AAAI 2025 · similarity 0.86)
- From Coarse to Fine-Grained Open-Set Recognition (CVPR 2024 · similarity 0.85)
- GUIDED: Granular Understanding via Identification, Detection, and Discrimination for Fine-Grained Open-Vocabulary Object Detection (NeurIPS 2025 · similarity 0.85)
- Democratizing Fine-grained Visual Recognition with Large Language Models (ICLR 2024 · similarity 0.84)
- Fine-grained Classes and How to Find Them (ICML 2024 · similarity 0.84)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.
