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The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
A resource for learning about Machine learning & Deep Learning
Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet…
TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data
Pytorch implementation of cnn network
[CVPR 2022--Oral] Restormer: Efficient Transformer for High-Resolution Image Restoration. SOTA for motion deblurring, image deraining, denoising (Gaussian/real data), and defocus deblurring.
Pytorch Lightning code guideline for conferences
Proper implementation of ResNet-s for CIFAR10/100 in pytorch that matches description of the original paper.
A PyTorch library and evaluation platform for end-to-end compression research
[CVPR 2023] Official code release of our paper "BiFormer: Vision Transformer with Bi-Level Routing Attention"
Implementation of 1D, 2D, and 3D FFT convolutions in PyTorch. Much faster than direct convolutions for large kernel sizes.
This repository contains the source code of our work on designing efficient CNNs for computer vision
Wavelet Convolutions for Large Receptive Fields. ECCV 2024.
[CADL'22, ECCVW] Official repository of paper titled "EdgeNeXt: Efficiently Amalgamated CNN-Transformer Architecture for Mobile Vision Applications".
Repository for "Deformable 3D Convolution for Video Super-Resolution", SPL, 2020
A Unified Implementation of Several Baseline Deep Learning Models for Automatic Modulation Recognition
A PyTorch implementation for PyramidNets (Deep Pyramidal Residual Networks, https://arxiv.org/abs/1610.02915)
Pytorch实现：使用ResNet18网络训练Cifar10数据集，测试集准确率达到95.46%(从0开始，不使用预训练模型)
Simulation of Digital Communication (physical layer) in Python.
Codes for "Deep Joint Source-Channel Coding for Wireless Image Transmission with Adaptive Rate Control", ICASSP 2022
Pytorch code for IEEE TWC paper "Predictive and Adaptive Deep Coding for Wireless Image Transmission in Semantic Communication"
[ICLR 2022] "Anti-Oversmoothing in Deep Vision Transformers via the Fourier Domain Analysis: From Theory to Practice" by Peihao Wang, Wenqing Zheng, Tianlong Chen, Zhangyang Wang
Joint Source Channel Coding of Images With Feedback