Semantic Segmentation Paper+Code大合集

Semantic Segmentation

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1. CCNet: Criss-Cross Attention for Semantic Segmentation - 2018  
2. A PyTorch Semantic Segmentation Toolbox - 2018  
3. ShelfNet for Real-time Semantic Segmentation - 2018  
4. Unsupervised Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training - ECCV2018   
5. Searching for Efficient Multi-Scale Architectures for Dense Image Prediction - 2018 - Deeplab  
6. Light-Weight RefineNet for Real-Time Semantic Segmentation - bmvc2018  
7. Dual Attention Network for Scene Segmentation - 2018 
8. BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation - ECCV 2018 - Face++ 
9. Adaptive Affinity Field for Semantic Segmentation - ECCV2018  
10. Dense Decoder Shortcut Connections for Single-Pass Semantic Segmentation - CVPR2018 
11. DenseASPP for Semantic Segmentation in Street Scenes - CVPR2018  
12. Pyramid Attention Network for Semantic Segmentation - 2018 - Face++ 
13. Autofocus Layer for Semantic Segmentation - 2018 
14. ExFuse: Enhancing Feature Fusion for Semantic Segmentation - ECCV2018 - Face++ 
15. DifNet: Semantic Segmentation by Diffusion Networks - 2018 
16. Convolutional CRFs for Semantic Segmentation - 2018 
17. ContextNet: Exploring Context and Detail for Semantic Segmentation in Real-time - 2018 
18. Learning a Discriminative Feature Network for Semantic Segmentation - CVPR2018 - Face++ 
19. Vortex Pooling: Improving Context Representation in Semantic Segmentation - 2018 
20. Fully Convolutional Adaptation Networks for Semantic Segmentation - CVPR2018 
21. A Multi-Layer Approach to Superpixel-based Higher-order Conditional Random Field for Semantic Image Segmentation - 2018 
22. Context Encoding for Semantic Segmentation - 2018   
23. ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation - ECCV2018  
24. Dynamic-structured Semantic Propagation Network - 2018 - CMU 
25. ShuffleSeg: Real-time Semantic Segmentation Network-2018  
26. RTSeg: Real-time Semantic Segmentation Comparative Study - 2018  
27. Decoupled Spatial Neural Attention for Weakly Supervised Semantic Segmentation - 2018 
28. DeepLabV3+:Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation - 2018 - Google   
29. Adversarial Learning for Semi-Supervised Semantic Segmentation - 2018  
30. Locally Adaptive Learning Loss for Semantic Image Segmentation - 2018 
31. Learning to Adapt Structured Output Space for Semantic Segmentation - 2018 
32. Improved Image Segmentation via Cost Minimization of Multiple Hypotheses - 2018  
33. TernausNet: U-Net with VGG11 Encoder Pre-Trained on ImageNet for Image Segmentation - 2018 - Kaggle   
34. Inverted Residuals and Linear Bottlenecks: Mobile Networks for Classification, Detection and Segmentation - 2018 - Google 
35. End-to-end Detection-Segmentation Network With ROI Convolution - 2018 
36. Mix-and-Match Tuning for Self-Supervised Semantic Segmentation - AAAI2018  
37. Learning to Segment Every Thing-2017   
38. Deep Dual Learning for Semantic Image Segmentation-2017 
39. Scene Parsing with Global Context Embedding - ICCV2017 
40. FoveaNet: Perspective-aware Urban Scene Parsing - ICCV2017 
41. Segmentation-Aware Convolutional Networks Using Local Attention Masks - 2017   
42. Stacked Deconvolutional Network for Semantic Segmentation-2017 
43. Semantic Segmentation via Structured Patch Prediction, Context CRF and Guidance CRF - CVPR2017  
44. BlitzNet: A Real-Time Deep Network for Scene Understanding-2017  
45. Efficient Yet Deep Convolutional Neural Networks for Semantic Segmentation -2017  
46. LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation - 2017 
47. Rethinking Atrous Convolution for Semantic Image Segmentation-2017(DeeplabV3) 
48. Learning Object Interactions and Descriptions for Semantic Image Segmentation-2017 
49. Pixel Deconvolutional Networks-2017  
50. Dilated Residual Networks-2017  
51. Recurrent Scene Parsing with Perspective Understanding in the Loop - 2017   
52. A Review on Deep Learning Techniques Applied to Semantic Segmentation-2017 
53. BiSeg: Simultaneous Instance Segmentation and Semantic Segmentation with Fully Convolutional Networks 
54. Efficient ConvNet for Real-time Semantic Segmentation - 2017 
55. ICNet for Real-Time Semantic Segmentation on High-Resolution Images-2017    
56. Not All Pixels Are Equal: Difficulty-Aware Semantic Segmentation via Deep Layer Cascade-2017     
57. Loss Max-Pooling for Semantic Image Segmentation-2017 
58. Annotating Object Instances with a Polygon-RNN-2017  
59. Feature Forwarding: Exploiting Encoder Representations for Efficient Semantic Segmentation-2017  
60. Reformulating Level Sets as Deep Recurrent Neural Network Approach to Semantic Segmentation-2017 
61. Adversarial Examples for Semantic Image Segmentation-2017 
62. Large Kernel Matters - Improve Semantic Segmentation by Global Convolutional Network-2017 
63. Label Refinement Network for Coarse-to-Fine Semantic Segmentation-2017 
64. PixelNet: Representation of the pixels, by the pixels, and for the pixels-2017   
65. LabelBank: Revisiting Global Perspectives for Semantic Segmentation-2017 
66. Progressively Diffused Networks for Semantic Image Segmentation-2017 
67. Understanding Convolution for Semantic Segmentation-2017   
68. Predicting Deeper into the Future of Semantic Segmentation-2017 
69. Pyramid Scene Parsing Network-2017    
70. FCNs in the Wild: Pixel-level Adversarial and Constraint-based Adaptation-2016 
71. FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics-2016  
72. RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation-2016   
73. Learning from Weak and Noisy Labels for Semantic Segmentation - 2017 
74. The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation    
75. Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes  
76. PixelNet: Towards a General Pixel-level Architecture-2016 
77. Recalling Holistic Information for Semantic Segmentation-2016 
78. Semantic Segmentation using Adversarial Networks-2016  
79. Region-based semantic segmentation with end-to-end training-2016 
80. Exploring Context with Deep Structured models for Semantic Segmentation-2016 
81. Better Image Segmentation by Exploiting Dense Semantic Predictions-2016 
82. Boundary-aware Instance Segmentation-2016 
83. Improving Fully Convolution Network for Semantic Segmentation-2016 
84. Deep Structured Features for Semantic Segmentation-2016 
85. DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs-2016     
86. DeepLab: Semantic Image Segmentation With Deep Convolutional Nets and Fully Connected CRFs-2014   
87. Deep Learning Markov Random Field for Semantic Segmentation-2016  
88. Convolutional Random Walk Networks for Semantic Image Segmentation-2016 
89. ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation-2016    
90. High-performance Semantic Segmentation Using Very Deep Fully Convolutional Networks-2016 
91. ScribbleSup: Scribble-Supervised Convolutional Networks for Semantic Segmentation-2016 
92. Object Boundary Guided Semantic Segmentation-2016  
93. Segmentation from Natural Language Expressions-2016    
94. Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation-2016  
95. Global Deconvolutional Networks for Semantic Segmentation-2016  
96. Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network-2015   
97. Learning Dense Convolutional Embeddings for Semantic Segmentation-2015 
98. ParseNet: Looking Wider to See Better-2015   
99. Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation-2015   
100. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation-2015     
101. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Robust Semantic Pixel-Wise Labelling-2015   
102. Semantic Image Segmentation with Task-Specific Edge Detection Using CNNs and a Discriminatively Trained Domain Transform-2015 
103. Semantic Segmentation with Boundary Neural Fields-2015  
104. Semantic Image Segmentation via Deep Parsing Network-2015    
105. What’s the Point: Semantic Segmentation with Point Supervision-2015    
106. U-Net: Convolutional Networks for Biomedical Image Segmentation-2015     
107. Learning Deconvolution Network for Semantic Segmentation(DeconvNet)-2015    
108. Multi-scale Context Aggregation by Dilated Convolutions-2015     
109. ReSeg: A Recurrent Neural Network-based Model for Semantic Segmentation-2015  
110. BoxSup: Exploiting Bounding Boxes to Supervise Convolutional Networks for Semantic Segmentation-2015 
111. Feedforward semantic segmentation with zoom-out features-2015   
112. Conditional Random Fields as Recurrent Neural Networks-2015      
113. Efficient Piecewise Training of Deep Structured Models for Semantic Segmentation-2015 
114. Fully Convolutional Networks for Semantic Segmentation-2015          
115. Deep Joint Task Learning for Generic Object Extraction-2014    
116. Highly Efficient Forward and Backward Propagation of Convolutional Neural Networks for Pixelwise Classification-2014  

Panoptic Segmentation

1. Panoptic Feature Pyramid Networks - 2019 
2. Panoptic Segmentation - 2018 

Human Parsing

1. Macro-Micro Adversarial Network for Human Parsing - ECCV2018  
2. Holistic, Instance-level Human Parsing - 2017 
3. Semi-Supervised Hierarchical Semantic Object Parsing - 2017 
4. Towards Real World Human Parsing: Multiple-Human Parsing in the Wild - 2017 
5. Look into Person: Self-supervised Structure-sensitive Learning and A New Benchmark for Human Parsing-2017   
6. Efficient and Robust Deep Networks for Semantic Segmentation - 2017   
7. Deep Learning for Human Part Discovery in Images-2016  
8. A CNN Cascade for Landmark Guided Semantic Part Segmentation-2016  
9. Deep Learning for Semantic Part Segmentation With High-level Guidance-2015 
10. Neural Activation Constellations-Unsupervised Part Model Discovery with Convolutional Networks-2015 
11. Human Parsing with Contextualized Convolutional Neural Network-2015 
12. Part detector discovery in deep convolutional neural networks-2014  

Clothes Parsing

1. Looking at Outfit to Parse Clothing-2017 
2. Semantic Object Parsing with Local-Global Long Short-Term Memory-2015 
3. A High Performance CRF Model for Clothes Parsing-2014    
4. Clothing co-parsing by joint image segmentation and labeling-2013   
5. Parsing clothing in fashion photographs-2012  

Instance Segmentation

1. A Pyramid CNN for Dense-Leaves Segmentation - 2018 
2. Predicting Future Instance Segmentations by Forecasting Convolutional Features - 2018 
3. Path Aggregation Network for Instance Segmentation - CVPR2018  
4. PixelLink: Detecting Scene Text via Instance Segmentation - AAAI2018  
5. MaskLab: Instance Segmentation by Refining Object Detection with Semantic and Direction Features - 2017 - google 
6. Recurrent Neural Networks for Semantic Instance Segmentation-2017 
7. Pixelwise Instance Segmentation with a Dynamically Instantiated Network-2017 
8. Semantic Instance Segmentation via Deep Metric Learning-2017 
9. Mask R-CNN-2017      
10. Pose2Instance: Harnessing Keypoints for Person Instance Segmentation-2017 
11. Pixelwise Instance Segmentation with a Dynamically Instantiated Network-2017 
12. Semantic Instance Segmentation with a Discriminative Loss Function-2017 
13. Fully Convolutional Instance-aware Semantic Segmentation-2016  
14. End-to-End Instance Segmentation with Recurrent Attention  
15. Instance-aware Semantic Segmentation via Multi-task Network Cascades-2015 
16. Recurrent Instance Segmentation-2015     

Segment Object Candidates

1. FastMask: Segment Object Multi-scale Candidates in One Shot-2016  
2. Learning to Refine Object Segments-2016  
3. Learning to Segment Object Candidates-2015   

Foreground Object Segmentation

1. Pixel Objectness-2017   
2. A Deep Convolutional Neural Network for Background Subtraction-2017 

 最后修改：2019 年 01 月 11 日 09 : 47 AM

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