Vehicle Re-identification on VeRi-Wild (test 3000)
92.65R1 AccuracyGiT
Evaluation results
| Method | Links | ||
|---|---|---|---|
| GiTArchitecture Category=Proposed2021.07 | 92.65 | 81.76 | |
| PCRNetArchitecture Category=Global + Local, Backbone Type=CNN & GN2021.07 | 92.5 | 81.2 | |
| GLAMORArchitecture Category=Global + Local, Backbone Type=Pure CNN2021.07 | 92.1 | 77.15 | |
| HPGN2020.05 | 91.37 | 80.42 | |
| HPGNArchitecture Category=Global + Local, Backbone Type=CNN & GN2021.07 | 91.37 | 80.42 | |
| ViTArchitecture Category=Transformer2021.07 | 89.29 | 78.66 | |
| UMTSArchitecture Category=Global + Local, Backbone Type=Pure CNN2021.07 | 84.5 | 72.7 | |
| Triplet Embedding2020.05 | 84.17 | 70.54 | |
| DFLNetArchitecture Category=Global + Local, Backbone Type=Pure CNN2021.07 | 80.68 | 68.21 | |
| AAVERArchitecture Category=Global + Local, Backbone Type=Pure CNN2021.07 | 75.8 | 62.23 | |
| FDA-Net2020.05 | 64.03 | 35.11 | |
| FDA-NetArchitecture Category=Global, Backbone Type=Pure CNN2021.07 | 64.03 | 35.11 | |
| GSTE2020.05 | 60.46 | 31.42 | |
| GSTEArchitecture Category=Global, Backbone Type=Pure CNN2021.07 | 60.46 | 31.42 | |
| Unlabled GAN2020.05 | 58.06 | 29.86 | |
| GoogLeNet2020.05 | 57.16 | 24.27 | |
| GoogLeNetArchitecture Category=Global, Backbone Type=Pure CNN2021.07 | 57.16 | 24.27 | |
| HDC2020.05 | 57.1 | 29.14 | |
| HDCArchitecture Category=Global, Backbone Type=Pure CNN2021.07 | 57.1 | 29.14 | |
| DRDL2020.05 | 56.96 | 22.5 | |
| DRDLArchitecture Category=Global, Backbone Type=Pure CNN2021.07 | 56.96 | 22.5 | |
| Softmax2020.05 | 53.4 | 26.41 | |
| SoftmaxArchitecture Category=Global, Backbone Type=Pure CNN2021.07 | 53.4 | 26.41 | |
| Triplet2020.05 | 44.67 | 15.69 | |
| TripletArchitecture Category=Global, Backbone Type=Pure CNN2021.07 | 44.67 | 15.69 |