From f480734ad5fb99f737142226db68921cc441ff45 Mon Sep 17 00:00:00 2001 From: Ross Wightman Date: Wed, 5 May 2021 23:17:35 -0700 Subject: [PATCH] Update README.md --- README.md | 20 ++++++++++++++++++++ 1 file changed, 20 insertions(+) diff --git a/README.md b/README.md index 4c7e0b57..166957ec 100644 --- a/README.md +++ b/README.md @@ -23,6 +23,20 @@ I'm fortunate to be able to dedicate significant time and money of my own suppor ## What's New +### May 5, 2021 +* Add MLP-Mixer models and port pretrained weights from [Google JAX impl](https://github.com/google-research/vision_transformer/tree/linen) +* Add CaiT models and pretrained weights from [FB](https://github.com/facebookresearch/deit) +* Add ResNet-RS models and weights from [TF](https://github.com/tensorflow/tpu/tree/master/models/official/resnet/resnet_rs). Thanks [Aman Arora](https://github.com/amaarora) +* Add CoaT models and weights. Thanks [Mohammed Rizin](https://github.com/morizin) +* Add new ImageNet-21k weights & finetuned weights for TResNet, MobileNet-V3, ViT models. Thanks [mrT](https://github.com/mrT23) +* Add GhostNet models and weights. Thanks [Kai Han](https://github.com/iamhankai) +* Update ByoaNet attention modles + * Improve SA module inits + * Hack together experimental stand-alone Swin based attn module and `swinnet` + * Consistent '26t' model defs for experiments. +* Add improved Efficientnet-V2S (prelim model def) weights. 83.8 top-1. +* WandB logging support + ### April 13, 2021 * Add Swin Transformer models and weights from https://github.com/microsoft/Swin-Transformer @@ -182,6 +196,8 @@ A full version of the list below with source links can be found in the [document * Big Transfer ResNetV2 (BiT) - https://arxiv.org/abs/1912.11370 * Bottleneck Transformers - https://arxiv.org/abs/2101.11605 +* CaiT (Class-Attention in Image Transformers) - https://arxiv.org/abs/2103.17239 +* CoaT (Co-Scale Conv-Attentional Image Transformers) - https://arxiv.org/abs/2104.06399 * CspNet (Cross-Stage Partial Networks) - https://arxiv.org/abs/1911.11929 * DeiT (Vision Transformer) - https://arxiv.org/abs/2012.12877 * DenseNet - https://arxiv.org/abs/1608.06993 @@ -192,11 +208,13 @@ A full version of the list below with source links can be found in the [document * EfficientNet AdvProp (B0-B8) - https://arxiv.org/abs/1911.09665 * EfficientNet (B0-B7) - https://arxiv.org/abs/1905.11946 * EfficientNet-EdgeTPU (S, M, L) - https://ai.googleblog.com/2019/08/efficientnet-edgetpu-creating.html + * EfficientNet V2 - https://arxiv.org/abs/2104.00298 * FBNet-C - https://arxiv.org/abs/1812.03443 * MixNet - https://arxiv.org/abs/1907.09595 * MNASNet B1, A1 (Squeeze-Excite), and Small - https://arxiv.org/abs/1807.11626 * MobileNet-V2 - https://arxiv.org/abs/1801.04381 * Single-Path NAS - https://arxiv.org/abs/1904.02877 +* GhostNet - https://arxiv.org/abs/1911.11907 * GPU-Efficient Networks - https://arxiv.org/abs/2006.14090 * Halo Nets - https://arxiv.org/abs/2103.12731 * HardCoRe-NAS - https://arxiv.org/abs/2102.11646 @@ -204,6 +222,7 @@ A full version of the list below with source links can be found in the [document * Inception-V3 - https://arxiv.org/abs/1512.00567 * Inception-ResNet-V2 and Inception-V4 - https://arxiv.org/abs/1602.07261 * Lambda Networks - https://arxiv.org/abs/2102.08602 +* MLP-Mixer - https://arxiv.org/abs/2105.01601 * MobileNet-V3 (MBConvNet w/ Efficient Head) - https://arxiv.org/abs/1905.02244 * NASNet-A - https://arxiv.org/abs/1707.07012 * NFNet-F - https://arxiv.org/abs/2102.06171 @@ -220,6 +239,7 @@ A full version of the list below with source links can be found in the [document * Semi-supervised (SSL) / Semi-weakly Supervised (SWSL) ResNet/ResNeXts - https://arxiv.org/abs/1905.00546 * ECA-Net (ECAResNet) - https://arxiv.org/abs/1910.03151v4 * Squeeze-and-Excitation Networks (SEResNet) - https://arxiv.org/abs/1709.01507 + * ResNet-RS - https://arxiv.org/abs/2103.07579 * Res2Net - https://arxiv.org/abs/1904.01169 * ResNeSt - https://arxiv.org/abs/2004.08955 * ReXNet - https://arxiv.org/abs/2007.00992