Research map / Label-efficient and robust learning / Domain adaptation and generalization
Style Normalization and Restitution for Generalizable Person Re-Identification
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 SNR modules to the ResNet-50 baseline | Baseline · Market1501→Duke | mAP: 19.8 -> 33.6 | Helped |
| Add SNR modules to the ResNet-50 baseline | Baseline · Duke→Market1501 | mAP: 21.8 -> 33.9 | Helped |
| Add Instance Normalization throughout the baseline | ResNet-50 ReID baseline · Market1501→Duke | mAP: 19.8 -> 24.1 | Helped |
| Add Instance Normalization throughout the baseline | ResNet-50 ReID baseline · Market1501→Market1501 | mAP: 82.8 -> 75.3 | Hurt |
| Add the dual causality loss (ablation) | SNR · Market1501→Duke | mAP: 26.1 -> 33.6 | Helped |
| Add the clarification loss (ablation) | SNR · Market1501→Duke | mAP: 28.8 -> 33.6 | Helped |
| Add the destruction loss (ablation) | SNR · Market1501→Duke | mAP: 28.0 -> 33.6 | Helped |
| Place SNR at all four stages instead of only one stage (ablation) | ResNet-50 · Market1501→Duke | mAP: 26.4 -> 33.6 | Helped |
| Replace content-adaptive gates with convolutional disentanglement (ablation) | SNR · Market1501→Duke | mAP: 29.7 -> 33.6 | Hurt |
| Use two unshared gates instead of complementary gates (ablation) | SNR · Market1501→Duke | mAP: 31.2 -> 33.6 | Hurt |
| Add SNR modules to the Baseline+MAR adaptation system | MAR-based ReID · Market1501 + unlabeled Duke→Duke | mAP: 35.2 -> 58.1 | Helped |
| Add more source datasets | Baseline-SNR · PRID | mAP: 39.0 -> 60.0 | Mixed |
Closest papers by meaning
- Person30K: A Dual-Meta Generalization Network for Person Re-Identification (CVPR 2021 · similarity 0.91)
- Generalizable Person Re-identification via Balancing Alignment and Uniformity (NeurIPS 2024 · similarity 0.88)
- From Poses to Identity: Training-Free Person Re-Identification via Feature Centralization (CVPR 2025 · similarity 0.88)
- Exploring the Camera Bias of Person Re-identification (ICLR 2025 · similarity 0.88)
- Diversity-Authenticity Co-constrained Stylization for Federated Domain Generalization in Person Re-identification (AAAI 2024 · similarity 0.87)
- ReID5o: Achieving Omni Multi-modal Person Re-identification in a Single Model (NeurIPS 2025 · similarity 0.87)
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.