Pinned Repositories
c-guo
CapsNet-Keras
A Keras implementation of CapsNet in NIPS2017 paper "Dynamic Routing Between Capsules". Now test error ＝ 0.34%.
CMC
[ECCV 2020] "Contrastive Multiview Coding", also contains implementations for MoCo and InstDis
DANet-keras
keras-Dual Attention Network for Scene Segmentation
ICCV2021-Paper-Code-Interpretation
ICCV2021/2019/2017 论文/代码/解读/直播合集，极市团队整理
Keras-DCL
This is a Keras implementation of the CVPR2019 paper "Destruction and Construction Learning for Fine-grained Image Recognition"
keras-grad-cam
An implementation of Grad-CAM with keras
LDAM-DRW
[NeurIPS 2019] Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss
pygcn
Graph Convolutional Networks in PyTorch
SupContrast
PyTorch implementation of "Supervised Contrastive Learning" (and SimCLR incidentally)
gcfengxu's Repositories
gcfengxu/c-guo
gcfengxu/CapsNet-Keras
A Keras implementation of CapsNet in NIPS2017 paper "Dynamic Routing Between Capsules". Now test error ＝ 0.34%.
gcfengxu/CMC
[ECCV 2020] "Contrastive Multiview Coding", also contains implementations for MoCo and InstDis
gcfengxu/DANet-keras
keras-Dual Attention Network for Scene Segmentation
gcfengxu/ICCV2021-Paper-Code-Interpretation
ICCV2021/2019/2017 论文/代码/解读/直播合集，极市团队整理
gcfengxu/Keras-DCL
This is a Keras implementation of the CVPR2019 paper "Destruction and Construction Learning for Fine-grained Image Recognition"
gcfengxu/keras-grad-cam
An implementation of Grad-CAM with keras
gcfengxu/LDAM-DRW
[NeurIPS 2019] Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss
gcfengxu/pygcn
Graph Convolutional Networks in PyTorch
gcfengxu/SupContrast
PyTorch implementation of "Supervised Contrastive Learning" (and SimCLR incidentally)
gcfengxu/TransFG
This is the official PyTorch implementation of the paper "TransFG: A Transformer Architecture for Fine-grained Recognition" (Ju He, Jie-Neng Chen, Shuai Liu, Adam Kortylewski, Cheng Yang, Yutong Bai, Changhu Wang, Alan Yuille).
gcfengxu/vit-pytorch
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
gcfengxu/yolov5
YOLOv5 in PyTorch > ONNX > CoreML > iOS