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Semantic Segmentation Papers

阿新 • • 發佈：2019-01-07
  1. Convolutional CRFs for Semantic Segmentation - 2018 [Paper] [Code-PyTorch]
  2. ContextNet: Exploring Context and Detail for Semantic Segmentation in Real-time - 2018 [Paper]
  3. Learning a Discriminative Feature Network for Semantic Segmentation - CVPR2018 - Face++ [Paper]
  4. Vortex Pooling: Improving Context Representation in Semantic Segmentation - 2018
    [Paper]
  5. Fully Convolutional Adaptation Networks for Semantic Segmentation - CVPR2018 [Paper]
  6. A Multi-Layer Approach to Superpixel-based Higher-order Conditional Random Field for Semantic Image Segmentation - 2018 [Paper]
  7. Context Encoding for Semantic Segmentation - 2018 [Paper] [Code-PyTorch]
  8. ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation - 2018
    [Paper]
  9. Dynamic-structured Semantic Propagation Network - 2018 - CMU [Paper]
  10. ShuffleSeg: Real-time Semantic Segmentation Network-2018 [Paper] [Code-TensorFlow]
  11. RTSeg: Real-time Semantic Segmentation Comparative Study - 2018 [Paper] [Code-TensorFlow]
  12. Decoupled Spatial Neural Attention for Weakly Supervised Semantic Segmentation - 2018
    [Paper]
  13. DeepLabV3+:Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation - 2018 - Google [Paper] [Code-Tensorflow] [Code-Karas]
  14. Adversarial Learning for Semi-Supervised Semantic Segmentation - 2018 [Paper] [Code-PyTorch]
  15. Locally Adaptive Learning Loss for Semantic Image Segmentation - 2018 [Paper]
  16. Learning to Adapt Structured Output Space for Semantic Segmentation - 2018 [Paper]
  17. Improved Image Segmentation via Cost Minimization of Multiple Hypotheses - 2018 [Paper] [Code-Matlab]
  18. Inverted Residuals and Linear Bottlenecks: Mobile Networks for Classification, Detection and Segmentation - 2018 - Google [Paper]
  19. End-to-end Detection-Segmentation Network With ROI Convolution - 2018 [Paper]
  20. Mix-and-Match Tuning for Self-Supervised Semantic Segmentation - AAAI2018 [Project] [Paper] [Code-Caffe]
  21. Deep Dual Learning for Semantic Image Segmentation-2017 [Paper]
  22. Scene Parsing with Global Context Embedding - 2017 - ICCV [Paper]
  23. FoveaNet: Perspective-aware Urban Scene Parsing - 2017 - ICCV [Paper]
  24. Segmentation-Aware Convolutional Networks Using Local Attention Masks - 2017 [Paper] [Code-Caffe] [Project]
  25. Stacked Deconvolutional Network for Semantic Segmentation-2017 [Paper]
  26. Semantic Segmentation via Structured Patch Prediction, Context CRF and Guidance CRF - CVPR2017 [Paper] [Caffe-Code]
  27. BlitzNet: A Real-Time Deep Network for Scene Understanding-2017 [Project] [Code-Tensorflow] [Paper]
  28. Efficient Yet Deep Convolutional Neural Networks for Semantic Segmentation -2017 [Paper] [Code-Caffe]
  29. LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation - 2017 [Paper] [Code-Torch]
  30. Rethinking Atrous Convolution for Semantic Image Segmentation-2017(DeeplabV3) [Paper]
  31. Learning Object Interactions and Descriptions for Semantic Image Segmentation-2017 [Paper]
  32. Recurrent Scene Parsing with Perspective Understanding in the Loop - 2017 [Project] [Paper] [Code-MatConvNet]
  33. A Review on Deep Learning Techniques Applied to Semantic Segmentation-2017 [Paper]
  34. BiSeg: Simultaneous Instance Segmentation and Semantic Segmentation with Fully Convolutional Networks [Paper]
  35. Efficient ConvNet for Real-time Semantic Segmentation - 2017 [Paper]
  36. ICNet for Real-Time Semantic Segmentation on High-Resolution Images-2017 [Project] [Code] [Paper] [Video]
  37. Not All Pixels Are Equal: Difficulty-Aware Semantic Segmentation via Deep Layer Cascade-2017 [Paper] [Poster] [Project]
  38. Loss Max-Pooling for Semantic Image Segmentation-2017 [Paper]
  39. Annotating Object Instances with a Polygon-RNN-2017 [Project] [Paper]
  40. Feature Forwarding: Exploiting Encoder Representations for Efficient Semantic Segmentation-2017 [Project] [Code-Torch7]
  41. Reformulating Level Sets as Deep Recurrent Neural Network Approach to Semantic Segmentation-2017 [Paper]
  42. Adversarial Examples for Semantic Image Segmentation-2017 [Paper]
  43. Large Kernel Matters - Improve Semantic Segmentation by Global Convolutional Network-2017 [Paper]
  44. Label Refinement Network for Coarse-to-Fine Semantic Segmentation-2017 [Paper]
  45. PixelNet: Representation of the pixels, by the pixels, and for the pixels-2017 [Project] [Code-Caffe] [Paper]
  46. LabelBank: Revisiting Global Perspectives for Semantic Segmentation-2017 [Paper]
  47. Progressively Diffused Networks for Semantic Image Segmentation-2017 [Paper]
  48. Understanding Convolution for Semantic Segmentation-2017 [Model-Mxnet] [Mxnet-Code] [Paper]
  49. Predicting Deeper into the Future of Semantic Segmentation-2017 [Paper]
  50. FCNs in the Wild: Pixel-level Adversarial and Constraint-based Adaptation-2016 [Paper]
  51. FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics-2016 [Code-PyTorch] [Paper]
  52. RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation-2016 [Code-MatConvNet] [Paper]
  53. Learning from Weak and Noisy Labels for Semantic Segmentation - 2017 [Paper]
  54. The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation [Code-Theano] [Code-Keras1] [Code-Keras2] [Paper]
  55. Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes [Code-Theano] [Paper]
  56. PixelNet: Towards a General Pixel-level Architecture-2016 [Paper]
  57. Recalling Holistic Information for Semantic Segmentation-2016 [Paper]
  58. Semantic Segmentation using Adversarial Networks-2016 [Paper] [Code-Chainer]
  59. Region-based semantic segmentation with end-to-end training-2016 [Paper]
  60. Exploring Context with Deep Structured models for Semantic Segmentation-2016 [Paper]
  61. Better Image Segmentation by Exploiting Dense Semantic Predictions-2016 [Paper]
  62. Boundary-aware Instance Segmentation-2016 [Paper]
  63. Improving Fully Convolution Network for Semantic Segmentation-2016 [Paper]
  64. Deep Structured Features for Semantic Segmentation-2016 [Paper]
  65. DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs-2016 [Project] [Code-Caffe] [Code-Tensorflow] [Code-PyTorch] [Paper]
  66. DeepLab: Semantic Image Segmentation With Deep Convolutional Nets and Fully Connected CRFs-2014 [Code-Caffe1] [Code-Caffe2] [Paper]
  67. Deep Learning Markov Random Field for Semantic Segmentation-2016 [Project] [Paper]
  68. Convolutional Random Walk Networks for Semantic Image Segmentation-2016 [Paper]
  69. ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation-2016 [Code-Caffe1][Code-Caffe2] [Paper] [Blog]
  70. High-performance Semantic Segmentation Using Very Deep Fully Convolutional Networks-2016 [Paper]
  71. ScribbleSup: Scribble-Supervised Convolutional Networks for Semantic Segmentation-2016 [Paper]
  72. Object Boundary Guided Semantic Segmentation-2016 [Code-Caffe] [Paper]
  73. Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation-2016 [Code-Caffe] [Paper]
  74. Global Deconvolutional Networks for Semantic Segmentation-2016 [Paper] [Code-Caffe]
  75. Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network-2015 [Project] [Code-Caffe] [Paper]
  76. Learning Dense Convolutional Embeddings for Semantic Segmentation-2015 [Paper]
  77. Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation-2015 [Project] [Code-Caffe] [Paper]
  78. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation-2015 [Project] [Code-Caffe] [Paper] [Tutorial1] [Tutorial2]
  79. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Robust Semantic Pixel-Wise Labelling-2015 [Code-Caffe] [Code-Chainer] [Paper]
  80. Semantic Image Segmentation with Task-Specific Edge Detection Using CNNs and a Discriminatively Trained Domain Transform-2015 [Paper]
  81. Semantic Segmentation with Boundary Neural Fields-2015 [Code] [Paper]
  82. Semantic Image Segmentation via Deep Parsing Network-2015 [Project] [Paper1] [Paper2] [Slides]
  83. Learning Deconvolution Network for Semantic Segmentation(DeconvNet)-2015 [Project] [Code-Caffe] [Paper] [Slides]
  84. ReSeg: A Recurrent Neural Network-based Model for Semantic Segmentation-2015 [Code-Theano] [Paper]
  85. BoxSup: Exploiting Bounding Boxes to Supervise Convolutional Networks for Semantic Segmentation-2015 [Paper]
  86. Feedforward semantic segmentation with zoom-out features-2015 [Code] [Paper] [Video]
  87. Efficient Piecewise Training of Deep Structured Models for Semantic Segmentation-2015 [Paper]
  88. Highly Efficient Forward and Backward Propagation of Convolutional Neural Networks for Pixelwise Classification-2014 [Code-Caffe] [Paper]

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