Research map / Label-efficient and robust learning / Recognition and long-tail
Real-World Person Re-Identification via Degradation Invariance 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 |
|---|---|---|---|
| Add degradation invariance learning (DIL) and degradation-guided attention (ablation) | DI-REID · CAVIAR | Rank-1: 44.6 -> 51.2 | Helped |
| Add the multi-scale structure (ablation) | DI-REID · CAVIAR | Rank-1: 47.2 -> 51.2 | Helped |
| Add degradation-guided attention (ablation) | DI-REID · CAVIAR | Rank-1: 48.0 -> 51.2 | Helped |
| Use both degradation-invariant and degradation-sensitive features instead of only degradation-invariant features (ablation) | DI-REID · CAVIAR | Rank-1: 41.0 -> 51.2 | Helped |
| Use both degradation-invariant and degradation-sensitive features instead of only degradation-sensitive features (ablation) | DI-REID · CAVIAR | Rank-1: 45.4 -> 51.2 | Helped |
Closest papers by meaning
- Learning Resolution-Invariant Deep Representations for Person Re-Identification (AAAI 2019 · similarity 0.89)
- Joint Discriminative and Generative Learning for Person Re-Identification (CVPR 2019 · similarity 0.89)
- Camera-Aware Proxies for Unsupervised Person Re-Identification (AAAI 2021 · similarity 0.88)
- Deep Low-Resolution Person Re-Identification (AAAI 2018 · similarity 0.87)
- Alice Benchmarks: Connecting Real World Re-Identification with the Synthetic (ICLR 2024 · similarity 0.87)
- Exploring the Camera Bias of Person Re-identification (ICLR 2025 · similarity 0.86)
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.