語義分割相關論文及復現代碼鏈接

來自專欄語義分割的學習5 人贊了文章

寫在前面：之前發現了一個網站上面有語義分割相關論文及代碼的鏈接總結，這裡我按所用深度學習框架給它進行了一點分類，方便大家學習。原文鏈接如下：https://www.aiuai.cn/aifarm62.html裡面還有不少好東西，如數據集等。也歡迎各位復現文章，然後把復現步驟總結好，發布到我的專欄，大家一起學習。分享是快樂的，因為一人分享一篇，十個人分享的話，那大家就相當於復現了十篇文章，這對大家學習還是有很大進步的。接下來，我也會嘗試復現一些文章代碼，然後寫好步驟，供大家一起學習交流。最後，祝大家早日登頂國際會議。另外，有人意見或者建議，歡迎在下方留言或者私信我。

Pytorch：

1.Autofocus Layer for Semantic Segmentation – 2018 [Paper [Code-PyTorch]

2.Convolutional CRFs for Semantic Segmentation – 2018 [Paper][Code-PyTorch]

3.Context Encoding for Semantic Segmentation – 2018 [Paper] [Code-PyTorch]

4.Adversarial Learning for Semi-Supervised Semantic Segmentation – 2018 [Paper] [Code-PyTorch]

5.TernausNet: U-Net with VGG11 Encoder Pre-Trained on ImageNet for Image Segmentation – 2018 – Kaggle [Paper] [Code-PyTorch] [Kaggle-Carvana Image Masking Challenge]

6.Learning to Segment Every Thing-2017 [Paper] [Code-Caffe2] [Code-PyTorch]

7.LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation – 2017 [Paper] [Code-Torch]

8.Dilated Residual Networks-2017 [Paper] [Code-PyTorch]

9.Feature Forwarding: Exploiting Encoder Representations for Efficient Semantic Segmentation-2017 [Project] [Code-Torch7]

10.FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics-2016 [Code-PyTorch] [Paper]

11.DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs-2016 [Project] [Code-Caffe] [Code-Tensorflow] [Code-PyTorch] [Paper]

12.Macro-Micro Adversarial Network for Human Parsing – ECCV2018 [Paper] [Code-PyTorch]

13.Learning to Refine Object Segments-2016 [Code-Torch] [Paper]

14.Recurrent Instance Segmentation-2015 [Project] [Code-Torch7] [Paper] [Poster] [Video]

15.Learning to Segment Object Candidates-2015 [Code-Torch] [Code-Theano-Keras] [Paper]

16.Fully Convolutional Networks for Semantic Segmentation-2015 [Code-Caffe] [Model-Caffe] [Code-Tensorflow1] [Code-Tensorflow2] [Code-Chainer] [Code-PyTorch] [Paper1] [Paper2] [Slides1] [Slides2]

Caffe:

1.Mix-and-Match Tuning for Self-Supervised Semantic Segmentation – AAAI2018 [Project] [Paper] [Code-Caffe]

2.Learning to Segment Every Thing-2017 [Paper] [Code-Caffe2] [Code-PyTorch]

3.Segmentation-Aware Convolutional Networks Using Local Attention Masks – 2017 [Paper] [Code-Caffe] [Project]

4. Semantic Segmentation via Structured Patch Prediction, Context CRF and Guidance CRF – CVPR2017 [Paper] [Caffe-Code]

5.Efficient Yet Deep Convolutional Neural Networks for Semantic Segmentation -2017 [Paper][Code-Caffe]

6.Not All Pixels Are Equal: Difficulty-Aware Semantic Segmentation via Deep Layer Cascade-2017 [Paper] [Poster] [Project] [Code-Caffe] [Slides]

7.PixelNet: Representation of the pixels, by the pixels, and for the pixels-2017 [Project] [Code-Caffe] [Paper]

8.Pyramid Scene Parsing Network-2017 [Project] [Code-Caffe] [Paper] [Slides]

9.DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs-2016 [Project] [Code-Caffe] [Code-Tensorflow] [Code-PyTorch] [Paper]

10.DeepLab: Semantic Image Segmentation With Deep Convolutional Nets and Fully Connected CRFs-2014 [Code-Caffe1] [Code-Caffe2] [Paper]

11.ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation-2016 [Code-Caffe1] [Code-Caffe2] [Paper] [Blog]

12.Object Boundary Guided Semantic Segmentation-2016 [Code-Caffe] [Paper]

13.Segmentation from Natural Language Expressions-2016 [Project] [Code-Tensorflow] [Code-Caffe] [Paper]

14.Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation-2016 [Code-Caffe] [Paper]

15.Global Deconvolutional Networks for Semantic Segmentation-2016 [Paper] [Code-Caffe]

16.Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network-2015 [Project] [Code-Caffe] [Paper]

17.ParseNet: Looking Wider to See Better-2015 [Code-Caffe] [Model-Caffe] [Paper]

18.Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation-2015 [Project] [Code-Caffe] [Paper]

19.SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation-2015 [Project] [Code-Caffe] [Paper] [Tutorial1] [Tutorial2]

20.SegNet: A Deep Convolutional Encoder-Decoder Architecture for Robust Semantic Pixel-Wise Labelling-2015 [Code-Caffe] [Code-Chainer] [Paper]

21.What』s the Point: Semantic Segmentation with Point Supervision-2015 [Project] [Code-Caffe] [Model-Caffe] [Paper]

22.Conditional Random Fields as Recurrent Neural Networks-2015 [Project] [Code-Caffe1] [Code-Caffe2] [Demo] [Paper1] [Paper2]

23.Fully Convolutional Networks for Semantic Segmentation-2015 [Code-Caffe] [Model-Caffe] [Code-Tensorflow1] [Code-Tensorflow2] [Code-Chainer] [Code-PyTorch] [Paper1] [Paper2] [Slides1] [Slides2]

24.Deep Joint Task Learning for Generic Object Extraction-2014 [Project] [Code-Caffe] [Dataset] [Paper]

25.Highly Efficient Forward and Backward Propagation of Convolutional Neural Networks for Pixelwise Classification-2014 [Code-Caffe] [Paper]

26.Look into Person: Self-supervised Structure-sensitive Learning and A New Benchmark for Human Parsing-2017 [Project] [Code-Caffe] [Paper]

27.Efficient and Robust Deep Networks for Semantic Segmentation – 2017 [Paper] [Project] [Code-Caffe]

28.MaskR-CNN-2017 [Code-Tensorflow] [Paper] [Code-Caffe2] [Code-Karas] [Code-PyTorch] [Code-MXNet]

29.FastMask: Segment Object Multi-scale Candidates in One Shot-2016 [Code-Caffe] [Paper]

30. Pixel Objectness-2017 [Project] [Code-Caffe] [Paper]

Tensorflow:

1.ShuffleSeg: Real-time Semantic Segmentation Network-2018 [Paper] [Code-TensorFlow]

2.RTSeg: Real-time Semantic Segmentation Comparative Study – 2018 [Paper] [Code-TensorFlow]

3.DeepLabV3+:Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation – 2018 – Google [Paper] [Code-Tensorflow] [Code-Karas]

4.BlitzNet: A Real-Time Deep Network for Scene Understanding-2017 [Project] [Code-Tensorflow] [Paper]

5.Pixel Deconvolutional Networks-2017 [Code-Tensorflow] [Paper]

6.DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs-2016 [Project] [Code-Caffe] [Code-Tensorflow] [Code-PyTorch] [Paper]

7.U-Net: Convolutional Networks for Biomedical Image Segmentation-2015 [Project] [Code+Data] [Code-Keras] [Code-Tensorflow] [Paper] [Notes]

8.Fully Convolutional Networks for Semantic Segmentation-2015 [Code-Caffe] [Model-Caffe] [Code-Tensorflow1] [Code-Tensorflow2] [Code-Chainer] [Code-PyTorch] [Paper1] [Paper2] [Slides1] [Slides2]

9.PixelLink: Detecting Scene Text via Instance Segmentation – AAAI2018 [Code-Tensorflow] [Paper]

10.Mask R-CNN-2017 [Code-Tensorflow] [Paper] [Code-Caffe2] [Code-Karas] [Code-PyTorch] [Code-MXNet]

11.End-to-End Instance Segmentation with Recurrent Attention [Paper] [Code-Tensorflow]

Others:

1.Improved Image Segmentation via Cost Minimization of Multiple Hypotheses – 2018 [Paper] [Code-Matlab]

2.Recurrent Scene Parsing with Perspective Understanding in the Loop – 2017 [Project] [Paper] [Code-MatConvNet]

3.Understanding Convolution for Semantic Segmentation-2017 [Model-Mxnet] [Mxnet-Code][Paper]

4.RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation-2016 [Code-MatConvNet] [Paper]

5.The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation [Code-Theano] [Code-Keras1] [Code-Keras2] [Paper]

6.Semantic Segmentation using Adversarial Networks-2016 [Paper] [Code-Chainer]

7.Deep Learning Markov Random Field for Semantic Segmentation-2016 [Project] [Paper]

8.Semantic Segmentation with Boundary Neural Fields-2015 [Code] [Paper]

9.ReSeg: A Recurrent Neural Network-based Model for Semantic Segmentation-2015 [Code-Theano] [Paper]

10.Feedforward semantic segmentation with zoom-out features-2015 [Code] [Paper] [Video]

11.Deep Learning for Human Part Discovery in Images-2016 [Code-Chainer] [Paper]

12.Part detector discovery in deep convolutional neural networks-2014 [Code] [Paper]

13.A High Performance CRF Model for Clothes Parsing-2014 [Project] [Code] [Dataset] [Paper]

14.Clothing co-parsing by joint image segmentation and labeling-2013 [Project] [Dataset] [Paper]

15.Parsing clothing in fashion photographs-2012 [Project] [Paper]

16.Fully Convolutional Instance-aware Semantic Segmentation-2016 [Code] [Paper]

17.Instance-aware Semantic Segmentation via Multi-task Network Cascades-2015 [Code] [Paper]

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