Pinned Repositories
2021-DIGIX-BASELINE
2021 huawei DIGIX competition baseline
awesome-image-classification
A curated list of deep learning image classification papers and codes
awesome-segmentation-saliency-dataset
A collection of some datasets for segmentation / saliency detection. Welcome to PR...:smile:
Awesome-Visual-Transformer
Collect some papers about transformer with vision. Awesome Transformer with Computer Vision (CV)
biblatex-map
bibmap 宏包和bibmap 后端程序用于生成参考文献和bib数据库修改。|| a backend like bibtex and a tool to modify the bib file, this tool is a partly python equivalent of the source map feature of biber
bottleneck-transformer-pytorch
Implementation of Bottleneck Transformer in Pytorch
convolution-vision-transformers
PyTorch Implementation of CvT: Introducing Convolutions to Vision Transformers
deep_matrix_factorization
Code for Implicit Regularization in Deep Matrix Factorization.
DWAN
The code complementary of the paper named Dual Wavelet Attention Networks for Image Classification
E-SRN
yutinyang's Repositories
yutinyang/DWAN
The code complementary of the paper named Dual Wavelet Attention Networks for Image Classification
yutinyang/2021-DIGIX-BASELINE
2021 huawei DIGIX competition baseline
yutinyang/awesome-image-classification
A curated list of deep learning image classification papers and codes
yutinyang/awesome-segmentation-saliency-dataset
A collection of some datasets for segmentation / saliency detection. Welcome to PR...:smile:
yutinyang/Awesome-Visual-Transformer
Collect some papers about transformer with vision. Awesome Transformer with Computer Vision (CV)
yutinyang/biblatex-map
bibmap 宏包和bibmap 后端程序用于生成参考文献和bib数据库修改。|| a backend like bibtex and a tool to modify the bib file, this tool is a partly python equivalent of the source map feature of biber
yutinyang/bottleneck-transformer-pytorch
Implementation of Bottleneck Transformer in Pytorch
yutinyang/convolution-vision-transformers
PyTorch Implementation of CvT: Introducing Convolutions to Vision Transformers
yutinyang/deep_matrix_factorization
Code for Implicit Regularization in Deep Matrix Factorization.
yutinyang/E-SRN
yutinyang/flops-counter.pytorch
Flops counter for convolutional networks in pytorch framework
yutinyang/FLRML
Fast Low-rank Metric Learning for Large-scale and High-dimensional Data
yutinyang/FSCN_AnomalyDetection
yutinyang/GraphWaveletNeuralNetwork
A PyTorch implementation of "Graph Wavelet Neural Network" (ICLR 2019)
yutinyang/kymatio
Wavelet scattering transforms in Python with GPU acceleration
yutinyang/mmsegmentation
OpenMMLab Semantic Segmentation Toolbox and Benchmark.
yutinyang/MSRN
yutinyang/pytorch-NMF
A pytorch package for non-negative matrix factorization.
yutinyang/pytorch_wavelets
Pytorch implementation of 2D Discrete Wavelet (DWT) and Dual Tree Complex Wavelet Transforms (DTCWT) and a DTCWT based ScatterNet
yutinyang/pywt
PyWavelets - Wavelet Transforms in Python
yutinyang/scene-graph-TF-release
"Scene Graph Generation by Iterative Message Passing" code repository
yutinyang/setr-pytorch
Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers
yutinyang/SETR-pytorch-1
Implementation of SETR model, Original paper: Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers.
yutinyang/SF-MSFormer
yutinyang/simple-cnaps
Source codes for "Improved Few-Shot Visual Classification" (CVPR 2020), "Enhancing Few-Shot Image Classification with Unlabelled Examples" (WACV 2022), and "Beyond Simple Meta-Learning: Multi-Purpose Models for Multi-Domain, Active and Continual Few-Shot Learning" (TPAMI 2022 - in submission)
yutinyang/Swin-Transformer
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
yutinyang/VIFB
Visible and Infrared Image Fusion Benchmark
yutinyang/vision
Datasets, Transforms and Models specific to Computer Vision
yutinyang/vit-pytorch
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
yutinyang/wavenet-pytorch
Learning optimal wavelet bases using a neural network approach in Pytorch