语义分割 - Semantic Segmentation PapersSemantic SegmentationPanoptic SegmentationHuman ParsingClothes ParsingInstance SegmentationSegment Object CandidatesForeground Object Segmentation

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我是靠谱客的博主开心月亮，最近开发中收集的这篇文章主要介绍语义分割 - Semantic Segmentation PapersSemantic SegmentationPanoptic SegmentationHuman ParsingClothes ParsingInstance SegmentationSegment Object CandidatesForeground Object Segmentation，觉得挺不错的，现在分享给大家，希望可以做个参考。

概述

版权归作者所有，仅供学习，我是一名搬运工。作者收集不错，存起来

http://www.aiuai.cn/aifarm62.html

Semantic Segmentation

Adaptive Affinity Field for Semantic Segmentation – ECCV2018 [Paper] [HomePage]
Pyramid Attention Network for Semantic Segmentation – 2018 – Face++ [Paper]
Autofocus Layer for Semantic Segmentation – 2018 [Paper [Code-PyTorch]
ExFuse: Enhancing Feature Fusion for Semantic Segmentation – 2018 – Face++ [Paper]
DifNet: Semantic Segmentation by Diffusion Networks – 2018 [Paper]
Convolutional CRFs for Semantic Segmentation – 2018 [Paper][Code-PyTorch]
ContextNet: Exploring Context and Detail for Semantic Segmentation in Real-time – 2018 [Paper]
Learning a Discriminative Feature Network for Semantic Segmentation – CVPR2018 – Face++ [Paper]
Vortex Pooling: Improving Context Representation in Semantic Segmentation – 2018 [Paper]
Fully Convolutional Adaptation Networks for Semantic Segmentation – CVPR2018 [Paper]
A Multi-Layer Approach to Superpixel-based Higher-order Conditional Random Field for Semantic Image Segmentation – 2018 [Paper]
Context Encoding for Semantic Segmentation – 2018 [Paper] [Code-PyTorch]
ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation – 2018 [Paper]
Dynamic-structured Semantic Propagation Network – 2018 – CMU [Paper]
ShuffleSeg: Real-time Semantic Segmentation Network-2018 [Paper] [Code-TensorFlow]
RTSeg: Real-time Semantic Segmentation Comparative Study – 2018 [Paper] [Code-TensorFlow]
Decoupled Spatial Neural Attention for Weakly Supervised Semantic Segmentation – 2018 [Paper]
DeepLabV3+:Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation – 2018 – Google [Paper] [Code-Tensorflow] [Code-Karas]
Adversarial Learning for Semi-Supervised Semantic Segmentation – 2018 [Paper] [Code-PyTorch]
Locally Adaptive Learning Loss for Semantic Image Segmentation – 2018 [Paper]
Learning to Adapt Structured Output Space for Semantic Segmentation – 2018 [Paper]
Improved Image Segmentation via Cost Minimization of Multiple Hypotheses – 2018 [Paper] [Code-Matlab]
TernausNet: U-Net with VGG11 Encoder Pre-Trained on ImageNet for Image Segmentation – 2018 – Kaggle [Paper] [Code-PyTorch] [Kaggle-Carvana Image Masking Challenge]
Inverted Residuals and Linear Bottlenecks: Mobile Networks for Classification, Detection and Segmentation – 2018 – Google [Paper]
End-to-end Detection-Segmentation Network With ROI Convolution – 2018 [Paper]
Mix-and-Match Tuning for Self-Supervised Semantic Segmentation – AAAI2018 [Project] [Paper] [Code-Caffe]
Learning to Segment Every Thing-2017 [Paper] [Code-Caffe2] [Code-PyTorch]
Deep Dual Learning for Semantic Image Segmentation-2017 [Paper]
Scene Parsing with Global Context Embedding – 2017 – ICCV [Paper]
FoveaNet: Perspective-aware Urban Scene Parsing – 2017 – ICCV [Paper]
Segmentation-Aware Convolutional Networks Using Local Attention Masks – 2017 [Paper] [Code-Caffe] [Project]
Stacked Deconvolutional Network for Semantic Segmentation-2017 [Paper]
Semantic Segmentation via Structured Patch Prediction, Context CRF and Guidance CRF – CVPR2017 [Paper] [Caffe-Code]
BlitzNet: A Real-Time Deep Network for Scene Understanding-2017 [Project] [Code-Tensorflow] [Paper]
Efficient Yet Deep Convolutional Neural Networks for Semantic Segmentation -2017 [Paper][Code-Caffe]
LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation – 2017 [Paper] [Code-Torch]
Rethinking Atrous Convolution for Semantic Image Segmentation-2017(DeeplabV3) [Paper]
Learning Object Interactions and Descriptions for Semantic Image Segmentation-2017 [Paper]
Pixel Deconvolutional Networks-2017 [Code-Tensorflow] [Paper]
Dilated Residual Networks-2017 [Paper] [Code-PyTorch]
Recurrent Scene Parsing with Perspective Understanding in the Loop – 2017 [Project] [Paper] [Code-MatConvNet]
A Review on Deep Learning Techniques Applied to Semantic Segmentation-2017 [Paper]
BiSeg: Simultaneous Instance Segmentation and Semantic Segmentation with Fully Convolutional Networks [Paper]
Efficient ConvNet for Real-time Semantic Segmentation – 2017 [Paper]
ICNet for Real-Time Semantic Segmentation on High-Resolution Images-2017 [Project] [Code] [Paper] [Video]
Not All Pixels Are Equal: Difficulty-Aware Semantic Segmentation via Deep Layer Cascade-2017 [Paper] [Poster] [Project] [Code-Caffe] [Slides]
Loss Max-Pooling for Semantic Image Segmentation-2017 [Paper]
Annotating Object Instances with a Polygon-RNN-2017 [Project] [Paper]
Feature Forwarding: Exploiting Encoder Representations for Efficient Semantic Segmentation-2017 [Project] [Code-Torch7]
Reformulating Level Sets as Deep Recurrent Neural Network Approach to Semantic Segmentation-2017 [Paper]
Adversarial Examples for Semantic Image Segmentation-2017 [Paper]
Large Kernel Matters – Improve Semantic Segmentation by Global Convolutional Network-2017 [Paper]
Label Refinement Network for Coarse-to-Fine Semantic Segmentation-2017 [Paper]
PixelNet: Representation of the pixels, by the pixels, and for the pixels-2017 [Project] [Code-Caffe] [Paper]
LabelBank: Revisiting Global Perspectives for Semantic Segmentation-2017 [Paper]
Progressively Diffused Networks for Semantic Image Segmentation-2017 [Paper]
Understanding Convolution for Semantic Segmentation-2017 [Model-Mxnet] [Mxnet-Code][Paper]
Predicting Deeper into the Future of Semantic Segmentation-2017 [Paper]
Pyramid Scene Parsing Network-2017 [Project] [Code-Caffe] [Paper] [Slides]
FCNs in the Wild: Pixel-level Adversarial and Constraint-based Adaptation-2016 [Paper]
FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics-2016 [Code-PyTorch] [Paper]
RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation-2016 [Code-MatConvNet] [Paper]
Learning from Weak and Noisy Labels for Semantic Segmentation – 2017 [Paper]
The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation [Code-Theano] [Code-Keras1] [Code-Keras2] [Paper]
Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes [Code-Theano] [Paper]
PixelNet: Towards a General Pixel-level Architecture-2016 [Paper]
Recalling Holistic Information for Semantic Segmentation-2016 [Paper]
Semantic Segmentation using Adversarial Networks-2016 [Paper] [Code-Chainer]
Region-based semantic segmentation with end-to-end training-2016 [Paper]
Exploring Context with Deep Structured models for Semantic Segmentation-2016 [Paper]
Better Image Segmentation by Exploiting Dense Semantic Predictions-2016 [Paper]
Boundary-aware Instance Segmentation-2016 [Paper]
Improving Fully Convolution Network for Semantic Segmentation-2016 [Paper]
Deep Structured Features for Semantic Segmentation-2016 [Paper]
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs-2016 [Project] [Code-Caffe] [Code-Tensorflow] [Code-PyTorch] [Paper]
DeepLab: Semantic Image Segmentation With Deep Convolutional Nets and Fully Connected CRFs-2014 [Code-Caffe1] [Code-Caffe2] [Paper]
Deep Learning Markov Random Field for Semantic Segmentation-2016 [Project] [Paper]
Convolutional Random Walk Networks for Semantic Image Segmentation-2016 [Paper]
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation-2016 [Code-Caffe1] [Code-Caffe2] [Paper] [Blog]
High-performance Semantic Segmentation Using Very Deep Fully Convolutional Networks-2016 [Paper]
ScribbleSup: Scribble-Supervised Convolutional Networks for Semantic Segmentation-2016 [Paper]
Object Boundary Guided Semantic Segmentation-2016 [Code-Caffe] [Paper]
Segmentation from Natural Language Expressions-2016 [Project] [Code-Tensorflow] [Code-Caffe] [Paper]
Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation-2016 [Code-Caffe] [Paper]
Global Deconvolutional Networks for Semantic Segmentation-2016 [Paper] [Code-Caffe]
Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network-2015 [Project] [Code-Caffe] [Paper]
Learning Dense Convolutional Embeddings for Semantic Segmentation-2015 [Paper]
ParseNet: Looking Wider to See Better-2015 [Code-Caffe] [Model-Caffe] [Paper]
Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation-2015 [Project] [Code-Caffe] [Paper]
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation-2015 [Project] [Code-Caffe] [Paper] [Tutorial1] [Tutorial2]
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Robust Semantic Pixel-Wise Labelling-2015 [Code-Caffe] [Code-Chainer] [Paper]
Semantic Image Segmentation with Task-Specific Edge Detection Using CNNs and a Discriminatively Trained Domain Transform-2015 [Paper]
Semantic Segmentation with Boundary Neural Fields-2015 [Code] [Paper]
Semantic Image Segmentation via Deep Parsing Network-2015 [Project] [Paper1] [Paper2] [Slides]
What’s the Point: Semantic Segmentation with Point Supervision-2015 [Project] [Code-Caffe] [Model-Caffe] [Paper]
U-Net: Convolutional Networks for Biomedical Image Segmentation-2015 [Project] [Code+Data] [Code-Keras] [Code-Tensorflow] [Paper] [Notes]
Learning Deconvolution Network for Semantic Segmentation(DeconvNet)-2015 [Project] [Code-Caffe] [Paper] [Slides]
Multi-scale Context Aggregation by Dilated Convolutions-2015 [Project] [Code-Caffe] [Code-Keras] [Paper] [Notes]
ReSeg: A Recurrent Neural Network-based Model for Semantic Segmentation-2015 [Code-Theano] [Paper]
BoxSup: Exploiting Bounding Boxes to Supervise Convolutional Networks for Semantic Segmentation-2015 [Paper]
Feedforward semantic segmentation with zoom-out features-2015 [Code] [Paper] [Video]
Conditional Random Fields as Recurrent Neural Networks-2015 [Project] [Code-Caffe1] [Code-Caffe2] [Demo] [Paper1] [Paper2]
Efficient Piecewise Training of Deep Structured Models for Semantic Segmentation-2015 [Paper]
Fully Convolutional Networks for Semantic Segmentation-2015 [Code-Caffe] [Model-Caffe] [Code-Tensorflow1] [Code-Tensorflow2] [Code-Chainer] [Code-PyTorch] [Paper1] [Paper2] [Slides1] [Slides2]
Deep Joint Task Learning for Generic Object Extraction-2014 [Project] [Code-Caffe] [Dataset] [Paper]
Highly Efficient Forward and Backward Propagation of Convolutional Neural Networks for Pixelwise Classification-2014 [Code-Caffe] [Paper]

Panoptic Segmentation

Panoptic Segmentation – 2018 [Paper]

Human Parsing

Macro-Micro Adversarial Network for Human Parsing – ECCV2018 [Paper] [Code-PyTorch]
Holistic, Instance-level Human Parsing – 2017 [Paper]
Semi-Supervised Hierarchical Semantic Object Parsing – 2017 [Paper]
Towards Real World Human Parsing: Multiple-Human Parsing in the Wild – 2017 [Paper]
Look into Person: Self-supervised Structure-sensitive Learning and A New Benchmark for Human Parsing-2017 [Project] [Code-Caffe] [Paper]
Efficient and Robust Deep Networks for Semantic Segmentation – 2017 [Paper] [Project] [Code-Caffe]
Deep Learning for Human Part Discovery in Images-2016 [Code-Chainer] [Paper]
A CNN Cascade for Landmark Guided Semantic Part Segmentation-2016 [Project] [Paper]
Deep Learning for Semantic Part Segmentation With High-level Guidance-2015 [Paper]
Neural Activation Constellations-Unsupervised Part Model Discovery with Convolutional Networks-2015 [Paper]
Human Parsing with Contextualized Convolutional Neural Network-2015 [Paper]
Part detector discovery in deep convolutional neural networks-2014 [Code] [Paper]

Clothes Parsing

Looking at Outfit to Parse Clothing-2017 [Paper]
Semantic Object Parsing with Local-Global Long Short-Term Memory-2015 [Paper]
A High Performance CRF Model for Clothes Parsing-2014 [Project] [Code] [Dataset] [Paper]
Clothing co-parsing by joint image segmentation and labeling-2013 [Project] [Dataset] [Paper]
Parsing clothing in fashion photographs-2012 [Project] [Paper]

Instance Segmentation

A Pyramid CNN for Dense-Leaves Segmentation – 2018 [Paper]
Predicting Future Instance Segmentations by Forecasting Convolutional Features – 2018 [Paper]
Path Aggregation Network for Instance Segmentation – CVPR2018 [Paper]
PixelLink: Detecting Scene Text via Instance Segmentation – AAAI2018 [Code-Tensorflow] [Paper]
MaskLab: Instance Segmentation by Refining Object Detection with Semantic and Direction Features – 2017 – google [Paper]
Recurrent Neural Networks for Semantic Instance Segmentation-2017 [Paper]
Pixelwise Instance Segmentation with a Dynamically Instantiated Network-2017 [Paper]
Semantic Instance Segmentation via Deep Metric Learning-2017 [Paper]
Mask R-CNN-2017 [Code-Tensorflow] [Paper] [Code-Caffe2] [Code-Karas] [Code-PyTorch] [Code-MXNet]
Pose2Instance: Harnessing Keypoints for Person Instance Segmentation-2017 [Paper]
Pixelwise Instance Segmentation with a Dynamically Instantiated Network-2017 [Paper]
Semantic Instance Segmentation with a Discriminative Loss Function-2017 [Paper]
Fully Convolutional Instance-aware Semantic Segmentation-2016 [Code] [Paper]
End-to-End Instance Segmentation with Recurrent Attention [Paper] [Code-Tensorflow]
Instance-aware Semantic Segmentation via Multi-task Network Cascades-2015 [Code] [Paper]
Recurrent Instance Segmentation-2015 [Project] [Code-Torch7] [Paper] [Poster] [Video]

Segment Object Candidates

FastMask: Segment Object Multi-scale Candidates in One Shot-2016 [Code-Caffe] [Paper]
Learning to Refine Object Segments-2016 [Code-Torch] [Paper]
Learning to Segment Object Candidates-2015 [Code-Torch] [Code-Theano-Keras] [Paper]