Rosun's repositories
STN_Pytorch
Implementation of Spatial Transformer Networks (STN)
AdaptSegNet
Learning to Adapt Structured Output Space for Semantic Segmentation, CVPR 2018 (spotlight)
AdvSemiSeg
Pytorch implementation of the paper "Adversarial Learning for Semi-supervised Semantic Segmentation," Wei-Chih Hung, Yi-Hsuan Tsai, Yan-Ting Liou, Yen-Yu Lin, and Ming-Hsuan Yang
CodingInterviewChinese2
《剑指Offer》第二版源代码
CVPR18-SFTGAN
Recovering Realistic Texture in Image Super-resolution by Deep Spatial Feature Transform (CVPR 2018) http://mmlab.ie.cuhk.edu.hk/projects/SFTGAN/
CycleGAN
Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.
DBPN-Pytorch
Deep Back-Projection Networks for Super-Resolution
DecoupledNet
DecoupledNet: Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation
deep-residual-networks
Deep Residual Learning for Image Recognition
DenseNet
Densely Connected Convolutional Networks, In CVPR 2017 (Best Paper Award).
extension-ffi
Examples of C extensions for PyTorch
pix2pixHD
Synthesizing and manipulating 2048x1024 images with conditional GANs
Pytorch-Deeplab
DeepLab-ResNet rebuilt in Pytorch
PyTorch-Multi-Style-Transfer
Neural Style and MSG-Net
pytorch-segmentation
Pytorch for Segmentation
pytorch-semantic-segmentation
PyTorch for Semantic Segmentation
pytorch-semseg
Semantic Segmentation Architectures Implemented in PyTorch
Single-Image-Super-Resolution
A collection of high-impact and state-of-the-art SR methods
SRGAN
A PyTorch implementation of SRGAN based on the paper "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network"
Super-Resolution.Benckmark
Benchmark and resources for single super-resolution algorithms
Synchronized-BatchNorm-PyTorch
Synchronized Batch Normalization implementation in PyTorch.
the-gan-zoo
A list of all named GANs!
topicsne
t-SNE experiments in pytorch
WINN
Wasserstein Introspective Neural Networks in Tensorflow
yolo-9000
YOLO9000: Better, Faster, Stronger - Real-Time Object Detection. 9000 classes!