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Sun Yat-sen University Cancer Center
- Guangzhou, Guangdong province
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All Algorithms implemented in Python
Tensors and Dynamic neural networks in Python with strong GPU acceleration
《动手学深度学习》:面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
PyTorch Tutorial for Deep Learning Researchers
Image-to-Image Translation in PyTorch
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
StyleGAN - Official TensorFlow Implementation
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
StyleGAN2 - Official TensorFlow Implementation
Tensorflow2.0 🍎🍊 is delicious, just eat it! 😋😋
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image …
OpenMMLab Semantic Segmentation Toolbox and Benchmark.
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
Synthesizing and manipulating 2048x1024 images with conditional GANs
Official PyTorch Implementation of "Scalable Diffusion Models with Transformers"
SwinIR: Image Restoration Using Swin Transformer (official repository)
NVIDIA's Deep Imagination Team's PyTorch Library
StarGAN v2 - Official PyTorch Implementation (CVPR 2020)
Denoising Diffusion Probabilistic Models
Release for Improved Denoising Diffusion Probabilistic Models
Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR
Multimodal Unsupervised Image-to-Image Translation
Unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners
Official PyTorch implementation of U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation
Contrastive unpaired image-to-image translation, faster and lighter training than cyclegan (ECCV 2020, in PyTorch)