Person Re Identification On Msmt17
Metriken
Rank-1
mAP
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Vergleichstabelle
| Modellname | Rank-1 | mAP |
|---|---|---|
| flipreid-closing-the-gap-between-training-and | 85.6 | 68.0 |
| enhancing-person-re-identification-via | 82.0 | 62.3 |
| disassembling-the-dataset-a-camera-alignment | 72.8 | 42.9 |
| an-effective-data-augmentation-for-person-re | 86.2 | 65.9 |
| self-supervised-pre-training-for-transformer | 89.6 | - |
| transreid-transformer-based-object-re | 86.20 | 69.40 |
| ca-jaccard-camera-aware-jaccard-distance-for | 86.2 | 74.1 |
| a-discriminatively-learned-cnn-embedding-for | 60.48 | 31.58 |
| unsupervised-person-re-identification-by-deep-1 | - | 12.5 |
| rethinking-person-re-identification-from-a | 85.4 | 65.5 |
| prototypical-contrastive-learning-based-clip | 89.8 | 76.1 |
| unihcp-a-unified-model-for-human-centric | - | 67.3 |
| git-graph-interactive-transformer-for-vehicle | 85.6 | 64.8 |
| devil-s-in-the-detail-graph-based-key-point | 83.54 | 62.00 |
| self-supervised-pre-training-for-transformer | 89.5 | 75.0 |
| circle-loss-a-unified-perspective-of-pair | 76.9 | 52.1 |
| unsupervised-tracklet-person-re | 31.4 | 13.1 |
| abd-net-attentive-but-diverse-person-re | 82.3 | 60.8 |
| enhancing-person-re-identification-via | 83.8 | 67.6 |
| msinet-twins-contrastive-search-of-multi | 81 | 59.6 |
| clip-reid-exploiting-vision-language-model | 89.7 | 75.8 |
| adaptivereid-adaptive-l2-regularization-in | 81.7 | 62.2 |
| person-re-identification-via-attention | 83.7 | 63.5 |
| adaptivereid-adaptive-l2-regularization-in | 84.9 | 76.7 |
| multi-task-learning-with-coarse-priors-for | 83.5 | 62.7 |
| beyond-appearance-a-semantic-controllable | 91.7 | 86.5 |
| large-scale-pre-training-for-person-re | 86.0 | 68.0 |
| omni-scale-feature-learning-for-person-re | 78.7 | 52.9 |
| circle-loss-a-unified-perspective-of-pair | 76.3 | 50.2 |
| rethinking-person-re-identification-from-a | 88.2 | 80 |
| learning-to-disentangle-scenes-for-person-re | 88.35 | 79.09 |
| prototypical-contrastive-learning-based-clip | 89.2 | 73.8 |
| counterfactual-attention-learning-for-fine | 84.2 | 64 |
| flipreid-closing-the-gap-between-training-and | 87.5 | 81.3 |
| deep-miner-a-deep-and-multi-branch-network | 85.60 | 67.30 |
| dip-learning-discriminative-implicit-parts | 87.3 | 71.8 |
| building-computationally-efficient-and-well | 77.97 | 48.66 |
| beyond-appearance-a-semantic-controllable | 90.7 | 77.1 |
| clip-reid-exploiting-vision-language-model | 91.1 | 86.7 |
| remix-training-generalized-person-re | 84.8 | 63.9 |
| unsupervised-pre-training-for-person-re | 86.6 | 68.8 |
| person-re-identification-in-the-3d-space | 47.71 | 23.01 |
| joint-discriminative-and-generative-learning | 77.2 | 52.3 |