# Designing Network Design Spaces ## Introduction ```latex @article{radosavovic2020designing, title={Designing Network Design Spaces}, author={Ilija Radosavovic and Raj Prateek Kosaraju and Ross Girshick and Kaiming He and Piotr Dollár}, year={2020}, eprint={2003.13678}, archivePrefix={arXiv}, primaryClass={cs.CV} } ``` ## Pretrain model The pre-trained modles are converted from [model zoo of pycls](https://github.com/facebookresearch/pycls/blob/master/MODEL_ZOO.md). ### ImageNet | Model | Params(M) | Flops(G) | Top-1 (%) | Top-5 (%) | Download | |:---------------------:|:---------:|:--------:|:---------:|:---------:|:--------:| | RegNetX-400MF | 5.16 | 0.41 | 72.55 | 90.91 | [model](https://download.openmmlab.com/mmclassification/v0/regnet/convert/RegNetX-400MF-0db9f35c.pth)| | RegNetX-800MF | 7.26 | 0.81 | 75.21 | 92.37 | [model](https://download.openmmlab.com/mmclassification/v0/regnet/convert/RegNetX-800MF-4f9d1e8a.pth)| | RegNetX-1.6GF | 9.19 | 1.63 | 77.04 | 93.51 | [model](https://download.openmmlab.com/mmclassification/v0/regnet/convert/RegNetX-1.6GF-cfb32375.pth)| | RegNetX-3.2GF | 15.3 | 3.21 | 78.26 | 94.20 | [model](https://download.openmmlab.com/mmclassification/v0/regnet/convert/RegNetX-3.2GF-82c43fd5.pth)| | RegNetX-4.0GF | 22.12 | 4.0 | 78.72 | 94.22 | [model](https://download.openmmlab.com/mmclassification/v0/regnet/convert/RegNetX-4.0GF-ef8bb32c.pth)| | RegNetX-6.4GF | 26.21 | 6.51 | 79.22 | 94.61 | [model](https://download.openmmlab.com/mmclassification/v0/regnet/convert/RegNetX-6.4GF-6888c0ea.pth)| | RegNetX-8.0GF | 39.57 | 8.03 | 79.31 | 94.57 | [model](https://download.openmmlab.com/mmclassification/v0/regnet/convert/RegNetX-8.0GF-cb4c77ec.pth)| | RegNetX-12GF | 46.11 | 12.15 | 79.91 | 94.78 | [model](https://download.openmmlab.com/mmclassification/v0/regnet/convert/RegNetX-12GF-0574538f.pth)| ## Results and models Waiting for adding.