Stars
Awesome List of Attention Modules and Plug&Play Modules in Computer Vision
A resource for learning about Machine learning & Deep Learning
deep learning for image processing including classification and object-detection etc.
This Repository is implementation of majority of Semantic Segmentation Loss Functions
A 8000 collection of loss functions for medical image segmentation
DeepLab v3+ model in PyTorch. Support different backbones.
The PyTorch improved version of TPAMI 2017 paper: Face Alignment in Full Pose Range: A 3D Total Solution.
This repository contains the source code for the paper First Order Motion Model for Image Animation
The Project is real time application in opencv using first order model
一本关于排序算法的 GitBook 在线书籍 《十大经典排序算法》，多语言实现。
Official tensorflow implementation for CVPR2020 paper “Learning to Cartoonize Using White-box Cartoon Representations”
PyTorch Implementation of ECCV 2020 Spotlight "TuiGAN: Learning Versatile Image-to-Image Translation with Two Unpaired Images"
Official repository for "TOAD-GAN: Coherent Style Level Generation from a Single Example" by Maren Awiszus, Frederik Schubert and Bodo Rosenhahn.
PyTorch implementation of "Improved Techniques for Training Single-Image GANs" (WACV-21)
Official pytorch implementation of the paper: "SinGAN: Learning a Generative Model from a Single Natural Image"
Unofficial PyTorch implementation of the paper titled "Progressive growing of GANs for improved Quality, Stability, and Variation"
A clean and readable Pytorch implementation of CycleGAN
Image-to-Image Translation in PyTorch
PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch：入门与实战》)
PyTorch implementations of Generative Adversarial Networks.
facenet recognition and retrieve by using hnswlib and flask, convert tensorflow model to caffe
The source code and dataset about <Deep Learning - Best Practices on TensorFlow Engineering Implementation>
simple implementation of SinGAN on tensorflow2.0
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06