The pre-trained diffusion model: 256x256_diffusion_uncond.pt from guided-diffusion
You can find configs and checkpoints of recognition models in mmclassification.
Specifically, the six models in our paper are shown as follows:
| Model | Pretrain | Params(M) | Flops(G) | Top-1 (%) | Top-5 (%) | Config | Download |
|---|---|---|---|---|---|---|---|
| RedNet-26 | From scratch | 9.23 | 1.73 | 75.96 | 93.19 | config | model | log |
| ResNet-50 | From scratch | 25.56 | 4.12 | 76.55 | 93.06 | config | model | log |
| Swin-T | From scratch | 28.29 | 4.36 | 81.18 | 95.61 | config | model | log |
| ConvNeXt-T | From scratch | 28.59 | 4.46 | 82.05 | 95.86 | config | model |
| Swin-B | From scratch | 87.77 | 15.14 | 83.36 | 96.44 | config | model | log |
| Swin-B | ImageNet-21k | 87.77 | 15.14 | 85.16 | 97.50 | config | model |
| ConvNeXt-B | From scratch | 88.59 | 15.36 | 83.85 | 96.74 | config | model |
| ConvNeXt-B | ImageNet-21k | 88.59 | 15.36 | 85.81 | 97.86 | config | model |