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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)

caffe

Caffe: a fast open framework for deep learning.

caffe-model

Caffe models (includimg classification, detection and segmentation) and deploy files for famouse networks

cec-corpus

:books:中文突发事件语料库（Chinese Emergency Corpus）-上海大学-语义智能实验室

confidence-adaptive-loss-for-stereo-matching

convolution_lstm_pytorch

Multi-layer convolutional LSTM with Pytorch

depth-estimation-from-stereo-and-video

A simple reproduction of Consistent Depth Maps Recovery from a Video Sequence based on MATLAB.

eppm

CUDA implementation of the paper "Fast Edge-Preserving PatchMatch for Large Displacement Optical Flow" in CVPR 2014.

esnet

ESNet: An Efficient Symmetric Network for Real-time Semantic Segmentation

face-swap

Face swapping, Image morphing, Image warping.

face_swap

End-to-end, automatic face swapping pipeline

faceswap

Non official project based on original /r/Deepfakes thread. Many thanks to him!

faceswap-gan

A denoising autoencoder + adversarial losses and attention mechanisms for face swapping.

fast_portrait_segmentation

Fast (aimed to "real time") Portrait Segmentation on mobile phone

faster_rcnn

Faster R-CNN

fd-fusion

Repository for the code related to the paper: Fast Stereo Disparity Maps Refinement By Fusion of Data-Based And Model-Based Estimations - 3DV 2019

flow-motion-depth

This is the project page of the paper "Flow-Motion and Depth Network for Monocular Stereo and Beyond''

geonet_pytorch

An unofficial PyTorch implementation of GeoNet

google-research

Google Research

guided-stereo

CVPR 2019 - Guided Stereo Matching

high-res-stereo

Hierarchical Deep Stereo Matching on High Resolution Images, CVPR 2019.

human-segmentation-pytorch

Human segmentation models, training/inference code, and trained weights, implemented in PyTorch

image2depth

imagebinarydataset

imagestable

Demo image stabilization software for SET challenge 2015

infix-to-postfix-using-stack

The main should take a string as input from user, convert it to postfix notation using infixToPostfix(), and then call evaluatePostfix(). Cases that must be handled in the program - Single digit numbers - Multi digit numbers - Brackets - Floating point numbers - Negative numbers

interpretablemlbook

《可解释的机器学习--黑盒模型可解释性理解指南》，该书为《Interpretable Machine Learning》中文版

iresnet

kitti_ssd

SSD detection for KITTI

kmp

Knuth–Morris–Pratt algorithm