Unsupervised Domain Adaptation On Duke To
평가 지표
mAP
rank-1
rank-10
rank-5
평가 결과
이 벤치마크에서 각 모델의 성능 결과
비교 표
| 모델 이름 | mAP | rank-1 | rank-10 | rank-5 |
|---|---|---|---|---|
| ad-cluster-augmented-discriminative | 68.3 | 86.7 | 96.5 | 94.4 |
| mutual-mean-teaching-pseudo-label-refinery-1 | 71.2 | 87.7 | 96.9 | 94.9 |
| transferable-joint-attribute-identity-deep | 26.5 | 58.2 | 81.1 | 74.8 |
| image-image-domain-adaptation-with-preserved | 22.8 | 51.5 | 76.8 | 70.1 |
| self-paced-contrastive-learning-with-hybrid | 76.7 | 90.3 | 97.7 | 96.2 |
| learning-to-adapt-invariance-in-memory-for | 63.8 | 84.1 | 95.4 | 92.8 |
| core-reid-comprehensive-optimization-and | 84.4 | 93.6 | 98.7 | 97.7 |
| style-normalization-and-restitution-for | 61.7 | 82.8 | - | - |
| unsupervised-domain-adaptive-re | 53.7 | 75.8 | 93.2 | 89.5 |
| unsupervised-and-self-adaptative-techniques | 78.4 | 92.9 | 97.8 | 96.9 |
| on-evolving-attention-towards-domain | 84.3 | - | - | - |
| disjoint-label-space-transfer-learning-with | 28.3 | 61.2 | - | - |
| joint-discriminative-and-generative-learning | 26.83 | 56.12 | 78.12 | 72.18 |
| adaptation-and-re-identification-network-an | 39.4 | 70.3 | 86.3 | 80.4 |
| person-re-identification-in-the-3d-space | 14.7 | 36.4 | - | - |
| learning-feature-fusion-for-unsupervised | 83.2 | 92.8 | - | - |
| self-training-with-progressive-augmentation | 54.6 | 78.4 | - | - |
| asymmetric-co-teaching-for-unsupervised-cross | 60.6 | 80.5 | - | - |
| structured-domain-adaptation-for-unsupervised | 70.0 | 86.9 | 96.3 | 94.4 |
| disassembling-the-dataset-a-camera-alignment | 52 | 81.7 | 94.7 | 91.9 |
| unsupervised-person-re-identification-via-1 | 60.4 | 84.4 | 95.0 | 92.8 |
| a-novel-unsupervised-camera-aware-domain | 30.9 | 60.4 | - | - |
| attentive-waveblock-complementarity-enhanced | 80.6 | 92.9 | 98.2 | 97.2 |
| 190909675 | 47.6 | 75.2 | 90.2 | 86.3 |
| invariance-matters-exemplar-memory-for-domain | 43.0 | 75.1 | - | - |
| one-shot-domain-adaptation-for-person-re | 58.3 | 80.0 | 92.4 | 90.0 |