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Semantic Segmentation

2019

  • Scale-Aware Trident Networks for Object Detection

    • Yanghao Li, Yuntao Chen, Naiyan Wang, Zhaoxiang Zhang
    • (arXiv: 1901)
  • Semantic Instance Meets Salient Object: Study on Video Semantic Salient Instance Segmentation

    • Trung-Nghia Le, Akihiro Sugimoto
    • (arXiv: 1807 | WACV 19)
  • Pixel-wise Attentional Gating for Scene Parsing

  • A New Ensemble Learning Framework for 3D Biomedical Image Segmentation

    • Hao Zheng, Yizhe Zhang, Lin Yang, Peixian Liang, Zhuo Zhao, Chaoli Wang, Danny Z. Chen
    • (arXiv:1812 | AAAI 19 | code)
  • Gradient Harmonized Single-stage Detector

2018

  • Multiview Cross-supervision for Semantic Segmentation

  • CCNet: Criss-Cross Attention for Semantic Segmentation

    • Z Huang, X Wang, L Huang, C Huang, Y Wei, W Liu
  • ShelfNet for Real-time Semantic Segmentation

  • See and Think: Disentangling Semantic Scene Completio [pytorch]

    • Shice Liu, YU HU, Yiming Zeng, Qiankun Tang, Beibei Jin, Yinhe Han, Xiaowei Li
    • (PDF | Supplemental | Poster)
  • Symbolic Graph Reasoning Meets Convolutions

  • Unsupervised domain adaptation for medical imaging segmentation with self-ensembling

    • Christian S. Perone, Pedro Ballester, Rodrigo C. Barros, Julien Cohen-Adad
    • (arXiv: 1811)
  • Scene Parsing via Dense Recurrent Neural Networks with Attentional Selection

    • Heng Fan, Peng Chu, Longin Jan Latecki, Haibin Ling
    • (arXiv: 1811)
  • Self-Erasing Network for Integral Object Attention

    • Qibin Hou, Peng-Tao Jiang, Yunchao Wei, Ming-Ming Cheng
    • (arXiv: 1810 | NIPS 18)
  • Smoothed Dilated Convolutions for Improved Dense Prediction [tensorflow]

  • Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells

    • Vladimir Nekrasov, Hao Chen, Chunhua Shen, Ian Reid
    • (arXiv: 1810)
    • NAS
  • Segmenting Unknown 3D Objects from Real Depth Images using Mask R-CNN Trained on Synthetic Point Clouds [temsorflow]

    • Michael Danielczuk, Matthew Matl, Saurabh Gupta, Andrew Li, Andrew Lee, Jeffrey Mahler, Ken Goldberg
    • (arXiv: 1809)
  • Searching for Efficient Multi-Scale Architectures for Dense Image Prediction [tensorflow]

    • Liang-Chieh Chen, M. D. Collins, Y. Zhu, G. Papandreou, B. Zoph, F. Schroff, H. Adam, J. Shlens
    • (arXiv: 1809 | NIPS 18)
    • deeplab, neural architecture search (NAS), meta learning
  • DifNet: Semantic Segmentation by Diffusion Networks

  • Autofocus Layer for Semantic Segmentation [pytorch]

    • Yao Qin, K. Kamnitsas, S. Ancha, J. Nanavati, G. Cottrell, A. Criminisi, A. Nori
    • (arXiv: 1805 | MICCAI 18)
  • Convolutional CRFs for Semantic Segmentation [pytorch]

    • Marvin T. T. Teichmann, Roberto Cipolla
    • (arXiv: 1805)
  • Context Encoding for Semantic Segmentation [pytorch]

  • Learning to Adapt Structured Output Space for Semantic Segmentation [pytorch]

    • Yi-Hsuan Tsai, W.-C. Hung, S. Schulter, K. Sohn, Ming-Hsuan Yang, M. Chandraker,
    • (arXiv: 1802 | CVPR 18 spotlight)
  • Weakly Supervised Instance Segmentation using Class Peak Response

    • Yanzhao Zhou, Yi Zhu, Qixiang Ye, Qiang Qiu, Jianbin Jiao
    • (arXiv: 1804 | CVPR 18 Spotligh | pytorch)
  • Learning a Discriminative Feature Network for Semantic Segmentation [pytorch] [temsorflow]

    • Changqian Yu, Jingbo Wang, Chao Peng, Changxin Gao, Gang Yu, Nong Sang,
    • (arXiv: 1804 | CVPR 18)
  • Recurrent Pixel Embedding for Instance Grouping [matlab]

  • Recurrent Scene Parsing with Perspective Understanding in the Loop [matlab]

  • Quantization of Fully Convolutional Networks for Accurate Biomedical Image Segmentation

    • Xiaowei Xu, Qing Lu, Lin Yang, Sharon Hu, Danny Chen, Yu Hu, Yiyu Shi
    • (arXiv: 1803 | CVPR 18)
  • Dense Decoder Shortcut Connections for Single-Pass Semantic Segmentation

    • Piotr Bilinski, Victor Prisacariu
    • CVPR 18
  • DenseASPP for Semantic Segmentation in Street Scenes [pytorch]

  • Dynamic-structured Semantic Propagation Network

  • Fully Convolutional Adaptation Networks for Semantic Segmentation

    • Yiheng Zhang, Zhaofan Qiu, Ting Yao, Dong Liu, Tao Mei
    • arXiv: 1804 | CVPR 18)
  • ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation [pytorch]

    • Sachin Mehta, Mohammad Rastegari, Anat Caspi, Linda Shapiro, Hannaneh Hajishirzi
    • (arXiv: 1803 | ECCV 18)
  • Adversarial Learning for Semi-supervised Semantic Segmentation [pytorch]

    • Wei-Chih Hung, Yi-Hsuan Tsai, Yan-Ting Liou, Yen-Yu Lin, and Ming-Hsuan Yang
    • (arXiv: 1802 | BMVC 18)
  • Light-Weight RefineNet for Real-Time Semantic Segmentation [pytorch]

    • Vladimir Nekrasov, Chunhua Shen, Ian Reid
    • (arXiv: 1810 | BMVC 18)
  • Multi-Scale Context Intertwining for Semantic Segmentation

    • Di Lin, Yuanfeng Ji, Dani Lischinski, Daniel Cohen-Or, Hui Huang
    • ECCV 18
    • [MSCI] Segmentation Results: VOC2012, mean: 88.0
  • Dual Attention Network for Scene Segmentation [pytorch]

    • Jun Fu, Jing Liu, Haijie Tian, Zhiwei Fang, Hanqing Lu
    • (arxiv: 1809 | AAAI19?)
  • BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation

    • Changqian Yu, Jingbo Wang, Chao Peng, Changxin Gao, Gang Yu, Nong Sang
    • arXiv: 1808 | ECCV 18)
  • Adaptive Affinity Field for Semantic Segmentation [tensorflow]

  • Pyramid Attention Network for Semantic Segmentation

    • Hanchao Li, Pengfei Xiong, Jie An, Lingxue Wang
    • (arXiv: 1805 | BMVC 18)
    • [PAN] Segmentation Results: VOC2012, mean: 84.0
  • ExFuse: Enhancing Feature Fusion for Semantic Segmentation [pytorch]

    • Zhenli Zhang, Xiangyu Zhang, Chao Peng, Dazhi Cheng, Jian Sun
    • (arXiv: 1804 | ECCV 18)
  • ContextNet: Exploring Context and Detail for Semantic Segmentation in Real-time [keras]

    • Rudra P K Poudel, Ujwal Bonde, Stephan Liwicki, Christopher Zach
    • (arXiv: 1805 | BMVC 18 | cn)
  • Vortex Pooling: Improving Context Representation in Semantic Segmentation

  • A Multi-Layer Approach to Superpixel-based Higher-order Conditional Random Field for Semantic Image Segmentation

    • Li Sulimowicz, Ishfaq Ahmad, Alexander Aved
    • (arXiv: 1804)
  • ShuffleSeg: Real-time Semantic Segmentation Network [tensorflow]

    • Mostafa Gamal, Mennatullah Siam, Moemen Abdel-Razek
    • (arXiv: 1803 | ICIP 18)
  • RTSeg: Real-time Semantic Segmentation Comparative Study [tensorflow]

    • Mennatullah Siam, Mostafa Gamal, M. Abdel-Razek, S. Yogamani, M. Jagersand
    • (arXiv: 1803 | ICIP 18)
  • Decoupled Spatial Neural Attention for Weakly Supervised Semantic Segmentation

    • Tianyi Zhang, Guosheng Lin, Jianfei Cai, Tong Shen, Chunhua Shen, Alex C. Kot
    • (arXiv: 1803)
  • Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation [tensorflow] [keras] [pytorch]

    • Liang-Chieh Chen, Yukun Zhu, George Papandreou, Florian Schroff, Hartwig Adam
    • (arXiv: 1802 | ECCV 18)
    • DeepLab v3+
  • Locally Adaptive Learning Loss for Semantic Image Segmentation

    • Jinjiang Guo, Pengyuan Ren, Aiguo Gu, Jian Xu, Weixin Wu
    • (arXiv: 1802)
  • TernausNet: U-Net with VGG11 Encoder Pre-Trained on ImageNet for Image Segmentation [PyTorch]

  • MobileNetV2: Inverted Residuals and Linear Bottlenecks

    • Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, Liang-Chieh Chen
    • (arXiv: 1801)
  • Mix-and-Match Tuning for Self-Supervised Semantic Segmentation [caffe]

    • Xiaohang Zhan, Ziwei Liu, Ping Luo, Xiaoou Tang, Chen Change Loy
    • (arXiv: 1712 | AAAI 18)
  • Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training [mxnet]

    • Yang Zou, Zhiding Yu, B. V. K. Vijaya Kumar, Jinsong Wang
    • (arXiv: 1810 | ECCV 18)
  • Joint Learning of Intrinsic Images and Semantic Segmentation

  • Characterizing Adversarial Examples Based on Spatial Consistency Information for Semantic Segmentation

    • Chaowei Xiao, Ruizhi Deng, Bo Li, Fisher Yu, Mingyan Liu, Dawn Song
    • (arXiv: 1810 | ECCV 18)
  • Effective Use of Synthetic Data for Urban Scene Semantic Segmentation

    • Fatemeh Sadat Saleh, Mohammad Sadegh Aliakbarian, Mathieu Salzmann, Lars Petersson, Jose M. Alvarez
    • (ECCV 18)
  • ICNet for Real-Time Semantic Segmentation on High-Resolution Images [caffe]

    • Hengshuang Zhao, Xiaojuan Qi, Xiaoyong Shen, Jianping Shi, Jiaya Jia
    • (arXiv: 1704 | ECCV 18 | project)
  • End-to-End Joint Semantic Segmentation of Actors and Actions in Video

    • Jingwei Ji, Shyamal Buch, Alvaro Soto, Juan Carlos Niebles
    • (ECCV 18)
  • Efficient Uncertainty Estimation for Semantic Segmentation in Videos [pytorch]

  • Multichannel Semantic Segmentation with Unsupervised Domain Adaptation

  • Kohei Watanabe, Kuniaki Saito, Yoshitaka Ushiku, Tatsuya Harada

  • (arXiv: | ECCV 18 workshop)

Object detection

  • Cascade Mask Generation Framework for Fast Small Object Detection

  • Efficient Coarse-to-Fine Non-Local Module for the Detection of Small Objects

  • Focal Loss in 3D Object Detection [tensorflow]

    • Peng Yun, Lei Tai, Yuan Wang, and Ming Liu
    • (arXiv:1809)
  • Receptive Field Block Net for Accurate and Fast Object Detection [RFBnet, pytorch]

  • Revisiting RCNN: On Awakening the Classification Power of Faster RCNN [mxnet]

    • Bowen Cheng, Yunchao Wei, Honghui Shi, Rogerio Feris, Jinjun Xiong, Thomas Huang
    • (arXiv: 1803 | ECCV 18)

others

  • SPFTN: A Joint Learning Framework for Localizing and Segmenting Objects in Weakly Labeled Videos
    • Dingwen Zhang ; Junwei Han ; Le Yang ; Dong Xu
    • (| TPAMI)

Bimedical

  • End-to-end Learning of Convolutional Neural Net and Dynamic Programming for Left Ventricle Segmentation

    • Nhat M. Nguyen, Nilanjan Ray
    • (arXiv)

2017

  • Adversarial Examples for Semantic Segmentation and Object Detection [caffe]

    • Cihang Xie, Jianyu Wang, Zhishuai Zhang, Yuyin Zhou, Lingxi Xie, Alan Yuille
    • (arXiv: 1703 | ICCV 17)
  • Learning to Segment Every Thing

  • Deep Dual Learning for Semantic Image Segmentation

    • Ping Luo, Guangrun Wang, Liang Lin, Xiaogang Wan, 2017
  • Scene Parsing with Global Context Embedding [caffe]

    • Wei-Chih Hung, Yi-Hsuan Tsai, X. Shen, Zhe Lin, K. Sunkavalli, X. Lu, and Ming-Hsuan Yang, ICCV/1710
  • FoveaNet: Perspective-aware Urban Scene Parsing

    • Xin Li, Zequn Jie, Wei Wang, Changsong Liu, Jimei Yang, Xiaohui Shen, Zhe Lin, Qiang Chen, Shuicheng Yan, Jiashi Feng
    • arXiv:1708.02421
    • ICCV 17
  • Segmentation-Aware Convolutional Networks Using Local Attention Masks - 2017

  • Stacked Deconvolutional Network for Semantic Segmentation-2017

  • Semantic Segmentation via Structured Patch Prediction, Context CRF and Guidance CRF [caffe]

    • Falong Shen, Rui Gan, Shuicheng Yan, Gang Zeng, CVPR/17 [cn]
  • [RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation [matlab]

  • BlitzNet: A Real-Time Deep Network for Scene Understanding

    • 2017
  • Efficient Yet Deep Convolutional Neural Networks for Semantic Segmentation

    • 2017
  • LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation

    • 2017
  • Rethinking Atrous Convolution for Semantic Image Segmentation

    • 2017(DeeplabV3)
  • Learning Object Interactions and Descriptions for Semantic Image Segmentation

    • 2017
  • Pixel Deconvolutional Networks

    • 2017
  • Dilated Residual Networks

    • 2017
  • Improved Image Segmentation via Cost Minimization of Multiple Hypotheses [BMVC, pdf][Matlab]

    • Marc Bosch, Christopher M. Gifford, Austin G. Dress, Clare W. Lau, Jeffrey G. Skibo, Gordon A. Christie, BMVC/17
  • A Review on Deep Learning Techniques Applied to Semantic Segmentation

    • 2017
  • BiSeg: Simultaneous Instance Segmentation and Semantic Segmentation with Fully Convolutional Networks

  • Efficient ConvNet for Real-time Semantic Segmentation - 2017

  • Not All Pixels Are Equal: Difficulty-Aware Semantic Segmentation via Deep Layer Cascade

    • 2017
  • Loss Max-Pooling for Semantic Image Segmentation

    • 2017
  • Annotating Object Instances with a Polygon-RNN

    • 2017
  • Feature Forwarding: Exploiting Encoder Representations for Efficient Semantic Segmentation

    • 2017
  • Reformulating Level Sets as Deep Recurrent Neural Network Approach to Semantic Segmentation

    • 2017
  • Adversarial Examples for Semantic Image Segmentation -2017

  • Large Kernel Matters - Improve Semantic Segmentation by Global Convolutional Network -2017

  • Label Refinement Network for Coarse-to-Fine Semantic Segmentation

    • 2017
  • PixelNet: Representation of the pixels, by the pixels, and for the pixels

    • 2017
  • LabelBank: Revisiting Global Perspectives for Semantic Segmentation

    • 2017
  • Progressively Diffused Networks for Semantic Image Segmentation

    • 2017
  • Understanding Convolution for Semantic Segmentation

    • 2017
  • Predicting Deeper into the Future of Semantic Segmentation -2017

  • Pyramid Scene Parsing Network [caffe]

    • Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, Jiaya Jia
    • PSPnet [project]

2016

  • FCNs in the Wild: Pixel-level Adversarial and Constraint-based Adaptation

    • 2016
  • FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics

    • 2016
  • Learning from Weak and Noisy Labels for Semantic Segmentation - 2017

  • The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation

  • Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes

  • PixelNet: Towards a General Pixel-level Architecture-2016

  • Recalling Holistic Information for Semantic Segmentation-2016

  • Semantic Segmentation using Adversarial Networks-2016

  • Region-based semantic segmentation with end-to-end training-2016

  • Exploring Context with Deep Structured models for Semantic Segmentation-2016

  • Better Image Segmentation by Exploiting Dense Semantic Predictions-2016

  • Boundary-aware Instance Segmentation-2016

  • Improving Fully Convolution Network for Semantic Segmentation-2016

  • Deep Structured Features for Semantic Segmentation-2016

  • Deep Learning Markov Random Field for Semantic Segmentation-2016

  • Convolutional Random Walk Networks for Semantic Image Segmentation-2016

  • ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation-2016

  • High-performance Semantic Segmentation Using Very Deep Fully Convolutional Networks-2016

  • ScribbleSup: Scribble-Supervised Convolutional Networks for Semantic Segmentation-2016

  • Object Boundary Guided Semantic Segmentation-2016

  • Segmentation from Natural Language Expressions-2016

  • Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation-2016

  • Global Deconvolutional Networks for Semantic Segmentation-2016

2015

2014

Panoptic Segmentation

  • Panoptic Segmentation - 2018

Human Parsing

2018

  • Macro-Micro Adversarial Network for Human Parsing - ECCV2018

2017

  • Holistic, Instance-level Human Parsing - 2017
  • Semi-Supervised Hierarchical Semantic Object Parsing - 2017
  • Towards Real World Human Parsing: Multiple-Human Parsing in the Wild - 2017
  • Look into Person: Self-supervised Structure-sensitive Learning and A New Benchmark for Human Parsing-2017
  • Efficient and Robust Deep Networks for Semantic Segmentation - 2017
  • Face Parsing via Recurrent Propagation
    • Sifei Liu, Jianping Shi, Ji Liang, Ming-Hsuan Yang, BMVC

2016

  • Deep Learning for Human Part Discovery in Images-2016
  • A CNN Cascade for Landmark Guided Semantic Part Segmentation-2016
  • Deep Learning for Semantic Part Segmentation With High-level Guidance-2015
  • Neural Activation Constellations-Unsupervised Part Model Discovery with Convolutional Networks-2015
  • Human Parsing with Contextualized Convolutional Neural Network-2015
  • Part detector discovery in deep convolutional neural networks-2014

Clothes Parsing

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

Instance Segmentation

  • Bayesian Semantic Instance Segmentation in Open Set World
    • Trung Pham, Vijay Kumar B. G., Thanh-Toan Do, Gustavo Carneiro, Ian Reid, ECCV/18
  • A Pyramid CNN for Dense-Leaves Segmentation - 2018
  • Predicting Future Instance Segmentations by Forecasting Convolutional Features - 2018
  • Path Aggregation Network for Instance Segmentation - CVPR2018
  • PixelLink: Detecting Scene Text via Instance Segmentation - AAAI2018
  • MaskLab: Instance Segmentation by Refining Object Detection with Semantic and Direction Features - 2017 - google
  • Recurrent Neural Networks for Semantic Instance Segmentation-2017
  • Pixelwise Instance Segmentation with a Dynamically Instantiated Network-2017
  • Semantic Instance Segmentation via Deep Metric Learning-2017
  • Mask R-CNN-2017
  • Pose2Instance: Harnessing Keypoints for Person Instance Segmentation-2017
  • Pixelwise Instance Segmentation with a Dynamically Instantiated Network-2017
  • Semantic Instance Segmentation with a Discriminative Loss Function-2017
  • Fully Convolutional Instance-aware Semantic Segmentation-2016
  • End-to-End Instance Segmentation with Recurrent Attention
  • Instance-aware Semantic Segmentation via Multi-task Network Cascades-2015
  • Recurrent Instance Segmentation-2015

Segment Object Candidates

  • FastMask: Segment Object Multi-scale Candidates in One Shot-2016
  • Learning to Refine Object Segments-2016
  • Learning to Segment Object Candidates-2015

Foreground Object Segmentation

  • Pixel Objectness-2017
  • A Deep Convolutional Neural Network for Background Subtraction-2017

Classic

Reference

Pytorch code

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License:MIT License