语义分割+视频分割开源代码集合

2018 年 3 月 5 日 极市平台 O天涯海阁O
语义分割+视频分割开源代码集合
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来源:CSDN博客(http://blog.csdn.net/zhangjunhit/article/details/78190283

语义分割 

Global Deconvolutional Networks 
BMVC 2016 
https://github.com/DrSleep/GDN


The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation CVPRW 2017 
Theano/Lasagne code Implementation 

https://github.com/0bserver07/One-Hundred-Layers-Tiramisu


Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes CVPR2017 
https://github.com/TobyPDE/FRRN


Awesome Semantic Segmentation 
https://github.com/mrgloom/awesome-semantic-segmentation


Semantic Segmentation Algorithms Implemented in PyTorch 这个很好! 
https://github.com/meetshah1995/pytorch-semseg


Learning Deconvolution Network for Semantic Segmentation 
https://github.com/HyeonwooNoh/DeconvNet


Fully Convolutional Instance-aware Semantic Segmentation 
https://github.com/daijifeng001/TA-FCN


Fully Convolutional Networks for Semantic Segmentation 
https://github.com/shelhamer/fcn.berkeleyvision.org


PixelNet: Representation of the pixels, by the pixels, and for the pixels 
https://github.com/aayushbansal/PixelNet 
http://www.cs.cmu.edu/~aayushb/pixelNet/


ICNet for Real-Time Semantic Segmentation on High-Resolution Images 
https://hszhao.github.io/projects/icnet/ https://github.com/hszhao/ICNet


SegNet: A Deep Convolutional Encoder-Decoder Architecture for Semantic Pixel-Wise Labelling 
https://arxiv.org/pdf/1511.00561.pdf 
PAMI-2017 
https://github.com/alexgkendall/caffe-segnet


DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs 
https://bitbucket.org/aquariusjay/deeplab-public-ver2/overview


DeconvNet : Learning Deconvolution Network for Semantic Segmentation ICCV2015 
https://github.com/HyeonwooNoh/DeconvNet http://cvlab.postech.ac.kr/research/deconvnet/


Pyramid Scene Parsing Network CVPR2017 
https://github.com/hszhao/PSPNet


Fully Convolutional Instance-aware Semantic Segmentation CVPR2017 
https://github.com/msracver/FCIS


ParseNet: Looking Wider to See Better 
https://github.com/weiliu89/caffe/tree/fcn


其他 

半监督语义分割 

Mix-and-Match Tuning for Self-Supervised Semantic Segmentation 
AAAI Conference on Artificial Intelligence (AAAI) 2018 
http://mmlab.ie.cuhk.edu.hk/projects/M&M/ 
https://github.com/XiaohangZhan/mix-and-match/


deconvnet analysis 
Salient Deconvolutional Networks ECCV2016 
https://github.com/aravindhm/deconvnet_analysis


Instance Segmentation 分水岭+CNN 
Deep Watershed Transform for Instance Segmentation CVPR2017 
https://github.com/min2209/dwt


Instance Segmentation 
End-to-End Instance Segmentation with Recurrent Attention CVPR2017 
https://github.com/renmengye/rec-attend-public


基于单张训练样本的视频运动物体分割 
Video Object Segmentation Without Temporal Information One-Shot Video Object Segmentation 
http://www.vision.ee.ethz.ch/~cvlsegmentation/osvos/


图像语义匹配 

SCNet: Learning Semantic Correspondence ICCV2017 
Matlab code: https://github.com/k-han/SCNet


同时检测和分割,类似 Mask R-CNN 
BlitzNet: A Real-Time Deep Network for Scene Understanding 
ICCV2017 

https://github.com/dvornikita/blitznet 


目标候选区域分割 

FastMask: Segment Multi-scale Object Candidates in One Shot CVPR2017 
https://github.com/voidrank/FastMask


视频分割

Learning to Segment Instances in Videos with Spatial Propagation Network CVPRW2017 
https://github.com/JingchunCheng/Seg-with-SPN


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相关内容

语义分割,在机器学习上,多指对一段文本或者一张图片,提取其中有意义的部分,我们将这些有意义的部分称为语义单元,将这些语义单元提取出来的过程,称为语义分割。

CVPR2020-Code

CVPR 2020 论文开源项目合集,同时欢迎各位大佬提交issue,分享CVPR 2020开源项目

图像分类

Spatially Attentive Output Layer for Image Classification

目标检测

Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection

BiDet: An Efficient Binarized Object Detector

3D目标检测

Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud

目标跟踪

MAST: A Memory-Augmented Self-supervised Tracker

语义分割

Cars Can't Fly up in the Sky: Improving Urban-Scene Segmentation via Height-driven Attention Networks

实例分割

PolarMask: Single Shot Instance Segmentation with Polar Representation

CenterMask : Real-Time Anchor-Free Instance Segmentation

Deep Snake for Real-Time Instance Segmentation

视频目标分割

State-Aware Tracker for Real-Time Video Object Segmentation

Learning Fast and Robust Target Models for Video Object Segmentation

NAS

Rethinking Performance Estimation in Neural Architecture Search

CARS: Continuous Evolution for Efficient Neural Architecture Search

GAN

Watch your Up-Convolution: CNN Based Generative Deep Neural Networks are Failing to Reproduce Spectral Distributions

Re-ID

Weakly supervised discriminative feature learning with state information for person identification

3D点云

点云卷积

FPConv: Learning Local Flattening for Point Convolution

3D点云配准

D3Feat: Joint Learning of Dense Detection and Description of 3D Local Features

人脸检测

活体检测

Searching Central Difference Convolutional Networks for Face Anti-Spoofing

人脸表情识别

Suppressing Uncertainties for Large-Scale Facial Expression Recognition

人体姿态估计

2D人体姿态估计

The Devil is in the Details: Delving into Unbiased Data Processing for Human Pose Estimation

Distribution-Aware Coordinate Representation for Human Pose Estimation

3D人体姿态估计

Compressed Volumetric Heatmaps for Multi-Person 3D Pose Estimation

VIBE: Video Inference for Human Body Pose and Shape Estimation

Back to the Future: Joint Aware Temporal Deep Learning 3D Human Pose Estimation

Cross-View Tracking for Multi-Human 3D Pose Estimation at over 100 FPS

点云

点云分类

PointAugment: an Auto-Augmentation Framework for Point Cloud Classification

场景文本检测

ABCNet: Real-time Scene Text Spotting with Adaptive Bezier-Curve Network

场景文本识别

ABCNet: Real-time Scene Text Spotting with Adaptive Bezier-Curve Network

超分辨率

视频超分辨率

Zooming Slow-Mo: Fast and Accurate One-Stage Space-Time Video Super-Resolution

模型剪枝

HRank: Filter Pruning using High-Rank Feature Map

行为识别

人群计数

深度估计

单目深度估计

Domain Decluttering: Simplifying Images to Mitigate Synthetic-Real Domain Shift and Improve Depth Estimation

去模糊

视频去模糊

Cascaded Deep Video Deblurring Using Temporal Sharpness Prior

视觉问答

视觉问答

VC R-CNN:Visual Commonsense R-CNN

视觉语言导航

Towards Learning a Generic Agent for Vision-and-Language Navigation via Pre-training

视频压缩

Learning for Video Compression with Hierarchical Quality and Recurrent Enhancement

行人轨迹预测

Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction

数据集

IntrA: 3D Intracranial Aneurysm Dataset for Deep Learning

Cross-View Tracking for Multi-Human 3D Pose Estimation at over 100 FPS

其他

GhostNet: More Features from Cheap Operations

AdderNet: Do We Really Need Multiplications in Deep Learning?

Deep Image Harmonization via Domain Verification

Blurry Video Frame Interpolation

Extremely Dense Point Correspondences using a Learned Feature Descriptor

Filter Grafting for Deep Neural Networks

Action Segmentation with Joint Self-Supervised Temporal Domain Adaptation

Detecting Attended Visual Targets in Video

Deep Image Spatial Transformation for Person Image Generation

Rethinking Zero-shot Video Classification: End-to-end Training for Realistic Applications

https://github.com/charlesCXK/3D-SketchAware-SSC

https://github.com/Anonymous20192020/Anonymous_CVPR5767

https://github.com/avirambh/ScopeFlow

https://github.com/csbhr/CDVD-TSP

https://github.com/ymcidence/TBH

https://github.com/yaoyao-liu/mnemonics

https://github.com/meder411/Tangent-Images

https://github.com/KaihuaTang/Scene-Graph-Benchmark.pytorch

https://github.com/sjmoran/deep_local_parametric_filters

https://github.com/charlesCXK/3D-SketchAware-SSC

https://github.com/bermanmaxim/AOWS

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