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Datasets, Transforms and Models specific to Computer Vision
Dual Attention Network for Scene Segmentation (CVPR2019)
PyTorch for Semantic Segmentation
CCNet: Criss-Cross Attention for Semantic Segmentation (TPAMI 2020 & ICCV 2019).
(Linear-chain) Conditional random field in PyTorch.
Files for a tutorial to train SegNet for road scenes using the CamVid dataset
Keras-tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation（Unfinished）
DeepLab resnet v2 model in pytorch
This repository contains the reference implementation for our proposed Convolutional CRFs.
Fully Convolutional DenseNets for semantic segmentation.
Implement some models of RGB/RGBD semantic segmentation in PyTorch, easy to run. Such as FCN, RefineNet, PSPNet, RDFNet, 3DGNN, PointNet, DeepLab V3, DeepLab V3 plus, DenseASPP, FastFCN
A playable implementation of Fully Convolutional Networks with Keras.
Train CRF-RNN for Semantic Image Segmentation
RGB-Thermal Fusion Network for Semantic Segmentation of Urban Scenes
A native Tensorflow implementation of semantic segmentation according to Multi-Scale Context Aggregation by Dilated Convolutions (2016). Optionally uses the pretrained weights by the authors.
MFNet-pytorch, image semantic segmentation using RGB-Thermal images
Using deeplabv3 and deeplabv3+ models to do stacking, and CRF.
Pytorch based implemenatation of Fully Convolutional Networks
pytorch implementation of DAG-Recurrent Neural Networks
Image segmentation for self-driving car. Based on Cityscapes dataset.
Denoising of noisy MNIST dataset images using Conditional Random Fields