Research map / Label-efficient and robust learning / Recognition and long-tail
Learning a Discriminative Null Space for Person Re-Identification
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Learn a discriminative null space instead of using XQDA with LOMO features | Person re-identification · VIPeR | Rank 1: 40.00 -> 42.28 | Helped |
| Fuse the two feature types at score level | Discriminative null-space re-identification · VIPeR | Rank 1: 42.28 -> 51.17 | Helped |
| Fuse two feature types | Discriminative null-space re-identification · PRID2011 | Rank 1: 29.80 -> 40.90 | Helped |
| Fuse two feature types | Discriminative null-space re-identification · CUHK01 | Rank 1: 64.98 -> 69.09 | Helped |
| Use the semi-supervised self-training extension with unlabelled data | NFST re-identification · PRID2011 | Rank 1 | Helped |
| Kernelise the null-space model | NFST re-identification · VIPeR | Rank 1 | Helped |
Closest papers by meaning
- A Bottom-Up Clustering Approach to Unsupervised Person Re-Identification (AAAI 2019 · similarity 0.90)
- Semi-Supervised Bayesian Attribute Learning for Person Re-Identification (AAAI 2018 · similarity 0.90)
- Point to Set Similarity Based Deep Feature Learning for Person Re-Identification (CVPR 2017 · similarity 0.90)
- Person30K: A Dual-Meta Generalization Network for Person Re-Identification (CVPR 2021 · similarity 0.89)
- Joint Discriminative and Generative Learning for Person Re-Identification (CVPR 2019 · similarity 0.89)
- From Poses to Identity: Training-Free Person Re-Identification via Feature Centralization (CVPR 2025 · similarity 0.87)
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