Table 8 Comparison of network accuracy (mAP and rank-1) and complexity (M: Parameters and T: GFLOPS) with different pruning scenarios on all the person ReID datasets. BFE backbone feature extractor; LC, local convolutional layer; FC, fully connected layer
| Â | Â | Market-1501 | DukeMTMC-reID | ||||||
|---|---|---|---|---|---|---|---|---|---|
Methods | Backbone | mAP | rank-1 | T | M | mAP | rank-1 | T | M |
PCB (Baseline) | Â | 77.3 | 92.4 | 6.1 | 27.2 | 65.3 | 81.9 | 6.1 | 27.2 |
PSFP + PCB (BFE) | ResNet50 | 69.4 | 90.4 | 2.6 | 12.0 | 60.7 | 78.5 | 2.6 | 12.0 |
PSFP + PCB (BFE+ LC + FC) | Â | 69.1 | 89.1 | 2.6 | 11.16 | 59.4 | 77.8 | 2.6 | 11.16 |
PCB (Baseline) | Â | 77.3 | 91.7 | 5.9 | 27.7 | 65.3 | 81.2 | 5.9 | 27.7 |
PSFP + PCB (BFE) | SE-ResNet50 | 70.0 | 88.4 | 2.59 | 14.5 | 61.9 | 78.9 | 2.59 | 14.5 |
PSFP + PCB (BFE+ LC + FC) | Â | 69.2 | 87.2 | 2.58 | 13.69 | 59.4 | 77.4 | 2.58 | 13.69 |