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adversarialnetspapers

The classical paper list with code about generative adversarial nets

awesome-multimodal-ml

Reading list for research topics in multimodal machine learning

awesome-semantic-segmentation-pytorch

Semantic Segmentation on PyTorch (include FCN, PSPNet, Deeplabv3, Deeplabv3+, DANet, DenseASPP, BiSeNet, EncNet, DUNet, ICNet, ENet, OCNet, CCNet, PSANet, CGNet, ESPNet, LEDNet, DFANet)

awesome-transformer-for-vision

bicyclegan

Toward Multimodal Image-to-Image Translation

bicyclegang

biggan-pytorch

The author's officially unofficial PyTorch BigGAN implementation.

bpnetwork

Moyan's BPNetwork

capsgnn

A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019).

ccnet

CCNet: Criss-Cross Attention for Semantic Segmentation (TPAMI 2020 & ICCV 2019).

cct

[CVPR 2020] Semi-Supervised Semantic Segmentation with Cross-Consistency Training.

ceal-medical-image-segmentation

Active Deep Learning for Medical Imaging Segmentation

chainer-caltech-101

An example of image classification with Chainer using 101_ObjectCategories

char-rnn.pytorch

PyTorch implementation of char-rnn (character-level language model)

chineseocr_lite

超轻量级中文ocr，支持竖排文字识别, 支持ncnn、mnn、tnn推理 ( dbnet(1.8M) + crnn(2.5M) + anglenet(378KB)) 总模型仅4.7M

cityscapes-segmentation-with-unet

Multiclass image segmentation in Keras

cityscapesscripts

README and scripts for the Cityscapes Dataset

clip

Contrastive Language-Image Pretraining

cmekg_labelingplatform

cmekg_tools

cmekgcrawler

Medical Graph for Neo4j

cocoapi

COCO API - Dataset @ http://cocodataset.org/

controlnet

Let us control diffusion models!

csbook

cvpr2021-paper-code-interpretation

cvpr2021/cvpr2020/cvpr2019/cvpr2018/cvpr2017 论文/代码/解读/直播合集，极市团队整理

dagcn

Dual Attention Graph Convolutional Network

deepin-wine-ubuntu

Deepin Wine for Ubuntu/Debian

deeplabv3plus-pytorch

DeepLabv3, DeepLabv3+ and pretrained weights on VOC & Cityscapes

delta_tb

Toolbox for the ONERA Delta project

denoisingdiffusionprobabilitymodel-ddpm-

This may be the simplest implement of DDPM. You can directly run Main.py to train the UNet on CIFAR-10 dataset and see the amazing process of denoising.