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113 lines
4.6 KiB
113 lines
4.6 KiB
# Model Architectures
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__FIXME - Clean This Up!__
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### ResNet / ResNeXt
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* ResNet-18, ResNet-34, ResNet-50, ResNet-101, ResNet-152, ResNeXt50 (32x4d), ResNeXt101 (32x4d and 64x4d)
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* 'Bag of Tricks' / Gluon C, D, E, S variations (https://arxiv.org/abs/1812.01187)
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* Instagram trained / ImageNet tuned ResNeXt101-32x8d to 32x48d from from [facebookresearch](https://pytorch.org/hub/facebookresearch_WSL-Images_resnext/)
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* Res2Net (https://github.com/gasvn/Res2Net, https://arxiv.org/abs/1904.01169)
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* Selective Kernel (SK) Nets (https://arxiv.org/abs/1903.06586)
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* ResNeSt (code adapted from https://github.com/zhanghang1989/ResNeSt, paper https://arxiv.org/abs/2004.08955)
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Originally based on ResNet from [torchvision](https://github.com/pytorch/vision/tree/master/torchvision/models)
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### DLA
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* Original
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* code: https://github.com/ucbdrive/dla
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* paper: https://arxiv.org/abs/1707.06484
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* Res2Net
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* code: https://github.com/gasvn/Res2Net
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* paper: https://arxiv.org/abs/1904.01169
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### DenseNet
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* DenseNet-121, DenseNet-169, DenseNet-201, DenseNet-161
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Code from [torchvision](https://github.com/pytorch/vision/tree/master/torchvision/models)
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### Squeeze-and-Excitation ResNet/ResNeXt
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* SENet-154, SE-ResNet-18, SE-ResNet-34, SE-ResNet-50, SE-ResNet-101, SE-ResNet-152, SE-ResNeXt-26 (32x4d), SE-ResNeXt50 (32x4d), SE-ResNeXt101 (32x4d)
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Code from [Cadene pretrained-models.pytorch](https://github.com/Cadene/pretrained-models.pytorch) with modifications
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### Inception-V3
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Code from [torchvision](https://github.com/pytorch/vision/tree/master/torchvision/models)
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### Inception-ResNet-V2 and Inception-V4
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Code from [Cadene pretrained-models.pytorch](https://github.com/Cadene/pretrained-models.pytorch)
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### Xception and Aligned-Xception (DeepLab)
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* Original variant from [Cadene pretrained-models.pytorch](https://github.com/Cadene/pretrained-models.pytorch)
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* MXNet Gluon 'modified aligned' Xception-65 and 71 models from [Gluon ModelZoo](https://github.com/dmlc/gluon-cv/tree/master/gluoncv/model_zoo)
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* DeepLab (Aligned) Xception-41, 65, and 71 from [Tensorflow Models](https://github.com/tensorflow/models/tree/master/research/deeplab)
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### PNasNet & NASNet-A
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Code from [Cadene pretrained-models.pytorch](https://github.com/Cadene/pretrained-models.pytorch)
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### DPN
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* DPN-68, DPN-68b, DPN-92, DPN-98, DPN-131, DPN-107
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Code adapted by [myself](https://github.com/rwightman/pytorch-dpn-pretrained) from MXNet originals (https://github.com/cypw/DPNs)
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### EfficientNet
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* EfficientNet NoisyStudent (B0-B7, L2) (https://arxiv.org/abs/1911.04252)
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* EfficientNet AdvProp (B0-B8) (https://arxiv.org/abs/1911.09665)
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* EfficientNet (B0-B7) (https://arxiv.org/abs/1905.11946)
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* EfficientNet-EdgeTPU (S, M, L) (https://ai.googleblog.com/2019/08/efficientnet-edgetpu-creating.html)
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* MixNet (https://arxiv.org/abs/1907.09595)
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* MNASNet B1, A1 (Squeeze-Excite), and Small (https://arxiv.org/abs/1807.11626)
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* MobileNet-V2 (https://arxiv.org/abs/1801.04381)
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* FBNet-C (https://arxiv.org/abs/1812.03443)
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* Single-Path NAS (https://arxiv.org/abs/1904.02877)
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Code from my standalone [GenEfficientNet](https://github.com/rwightman/gen-efficientnet-pytorch), adapted from [Tensorflow originals](https://github.com/tensorflow/tpu/tree/master/models/official/efficientnet).
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### MobileNet-V3
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* MobileNetV3-Large, MobileNetV3-Small (https://arxiv.org/abs/1905.02244)
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Code from my standalone [GenEfficientNet](https://github.com/rwightman/gen-efficientnet-pytorch), adapted from [Tensorflow originals](https://github.com/tensorflow/models/tree/master/research/slim/nets/mobilenet).
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### HRNet
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* code from https://github.com/HRNet/HRNet-Image-Classification
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* paper https://arxiv.org/abs/1908.07919
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### SelecSLS
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* paper https://arxiv.org/abs/1907.00837
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* code from https://github.com/mehtadushy/SelecSLS-Pytorch
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### TResNet
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* paper https://arxiv.org/abs/2003.13630
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* code from https://github.com/mrT23/TResNet
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### RegNet
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* paper `Designing Network Design Spaces` - https://arxiv.org/abs/2003.13678
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* reference code at https://github.com/facebookresearch/pycls/blob/master/pycls/models/regnet.py
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### VovNet V2 / V1
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* paper `CenterMask : Real-Time Anchor-Free Instance Segmentation` - https://arxiv.org/abs/1911.06667
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* reference code at https://github.com/youngwanLEE/vovnet-detectron2
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### CspNet (Cross-Stage Partial Networks)
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* paper `CSPNet: A New Backbone that can Enhance Learning Capability of CNN` - https://arxiv.org/abs/1911.11929
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* reference impl at https://github.com/WongKinYiu/CrossStagePartialNetworks
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### ReXNet
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* paper `ReXNet: Diminishing Representational Bottleneck on CNN` - https://arxiv.org/abs/2007.00992
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* code from https://github.com/clovaai/rexnet
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