| swin_s                         |    83.196 |     96.36 |
| swin_b                         |    83.582 |     96.64 |
| efficientnet_v2_s              |    84.228 |    96.878 |
| efficientnet_v2_m              |    85.112 |    97.156 |
| efficientnet_v2_l              |    85.808 |    97.788 |
| resnext101_64x4d               |    83.246 |    96.454 |
| resnext101_64x4d (quantized)   |    82.898 |    96.326 |
| shufflenet_v2_x1_5             |    72.996 |    91.086 |
| shufflenet_v2_x1_5 (quantized) |    72.052 |     0.700 |
| shufflenet_v2_x2_0             |    76.230 |    93.006 |
| shufflenet_v2_x2_0 (quantized) |    75.354 |    92.488 |
| mnasnet0_75                    |    71.180 |    90.496 |
| mnas1_3                        |    76.506 |    93.522 |
We would like to thank Hu Ye for contributing to TorchVision the Swin Transformer implementation.
(BETA) Object Detection and Instance Segmentation