fast-reid/MODEL_ZOO.md

125 lines
3.1 KiB
Markdown

# FastReID Model Zoo and Baselines
## Introduction
### Market1501 Baselines
**BoT**:
| Method | Pretrained | Rank@1 | mAP | mINP |
| :---: | :---: | :---: |:---: | :---: |
| BoT(R50) | ImageNet | 93.6% | 85.1% | 58.1% |
| BoT(R50-ibn) | ImageNet | 94.8% | 87.3% | 63.5% |
| BoT(S50) | ImageNet | - | - | - |
| BoT(R101-ibn) | ImageNet| - | - |
**AGW**:
| Method | Pretrained | Rank@1 | mAP | mINP |
| :---: | :---: | :---: |:---: | :---: |
| AGW(R50) | ImageNet | 94.9% | 87.4% | 63.1% |
| AGW(R50-ibn) | ImageNet | - | - | - |
| AGW(R101-ibn) | ImageNet | - | - | - |
**SBS**:
| Method | Pretrained | Rank@1 | mAP | mINP |
| :---: | :---: | :---: |:---: | :---: |
| SBS(R50) | ImageNet | - | - | - |
| SBS(R50-ibn) | ImageNet | 95.5% | 88.4% | 65.8% |
| SBS(S50) | ImageNet | - | - | - |
| SBS(R101-ibn) | ImageNet | - | - | - |
### DukeMTMC Baseline
**BoT**:
| Method | Pretrained | Rank@1 | mAP | mINP |
| :---: | :---: | :---: |:---: | :---: |
| BoT(R50) | ImageNet | 86.1% | 75.9% | 38.7% |
| BoT(R50-ibn) | ImageNet | 89.0% | 78.8% | 43.6% |
| BoT(S50) | ImageNet | - | - | - |
| BoT(R101-ibn) | ImageNet| - | - |
**AGW**:
| Method | Pretrained | Rank@1 | mAP | mINP |
| :---: | :---: | :---: |:---: | :---: |
| AGW(R50) | ImageNet | 88.9% | 79.1% | 43.2% |
| AGW(R50-ibn) | ImageNet | - | - | - |
| AGW(R101-ibn) | ImageNet | - | - | - |
**SBS**:
| Method | Pretrained | Rank@1 | mAP | mINP |
| :---: | :---: | :---: |:---: | :---: |
| SBS(R50) | ImageNet | - | - | - |
| SBS(R50-ibn) | ImageNet | 91.3% | 81.6% | 47.6% |
| SBS(S50) | ImageNet | - | - | - |
| SBS(R101-ibn) | ImageNet | - | - | - |
### MSMT17 Baseline
**BoT**:
| Method | Pretrained | Rank@1 | mAP | mINP |
| :---: | :---: | :---: |:---: | :---: |
| BoT(R50) | ImageNet | 70.4% | 47.5% | 9.6% |
| BoT(R50-ibn) | ImageNet | 76.9% | 55.0% | 13.5% |
| BoT(S50) | ImageNet | - | - | - |
| BoT(R101-ibn) | ImageNet| - | - |
**AGW**:
| Method | Pretrained | Rank@1 | mAP | mINP |
| :---: | :---: | :---: |:---: | :---: |
| AGW(R50) | ImageNet | 75.6% | 52.6% | 11.9% |
| AGW(R50-ibn) | ImageNet | - | - | - |
| AGW(R101-ibn) | ImageNet | - | - | - |
**SBS**:
| Method | Pretrained | Rank@1 | mAP | mINP |
| :---: | :---: | :---: |:---: | :---: |
| SBS(R50) | ImageNet | - | - | - |
| SBS(R50-ibn) | ImageNet | 84.2% | 61.5% | 15.7% |
| SBS(S50) | ImageNet | - | - | - |
| SBS(R101-ibn) | ImageNet | - | - | - |
### VeRi Baseline
**BoT**:
| Method | Pretrained | Rank@1 | mAP | mINP |
| :---: | :---: | :---: |:---: | :---: |
| BoT(R50-ibn) | ImageNet | 96.1% | 78.8% | 43.8% |
### VehicleID Baseline
**BoT**:
Method: BoT(R50-ibn)
| Testset size | Pretrained | Rank@1 | mAP | mINP |
| :---: | :---: | :---: |:---: | :---: |
| Small(800) | ImageNet | 95.5% | 89.5% | 77.0% |
| Medium(1600) | ImageNet | 93.8% | 85.6% | 69.4% |
| Large(2400) | ImageNet | 93.3% | 84.1% | 67.4% |
### VERI-Wild Baseline
**BoT**:
Method: BoT(R50-ibn)
| Testset size | Pretrained | Rank@1 | mAP | mINP |
| :---: | :---: | :---: |:---: | :---: |
| Small(3000) | ImageNet | 96.4% | 87.7% | 69.2% |
| Medium(5000) | ImageNet | 95.1% | 83.5% | 61.2% |
| Large(10000) | ImageNet | 92.5% | 77.3% | 49.8% |