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In previous deep-learning-based methods, semantic segmentation has been regarded as a static or dynamic per-pixel classification task, \textit{i.e.,} classify each pixel representation to a specific category.
Enhancing human-computer interaction in medical segmentation
Matthias Harders and Gabor Szekely · 2003
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Fully convolutional networks for semantic segmentation
Jonathan Long, Evan Shelhamer, and Trevor Darrell · 2015
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The cityscapes dataset for semantic urban scene understanding
Marius Cordts, Mohamed Omran, Sebastian Ramos, Timo Rehfeld, Markus Enzweiler, Rodrigo Benenson, Uwe Franke, Stefan Roth, and Bernt Schiele · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Identity mappings in deep residual networks
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Augmented reality meets deep learning for car instance segmentation in urban scenes
Hassan Abu Alhaija, Siva Karthik Mustikovela, Lars Mescheder, Andreas Geiger, and Carsten Rother · 2017
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Rethinking atrous convolution for semantic image segmentation
Liang-Chieh Chen, George Papandreou, Florian Schroff, and Hartwig Adam · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Pyramid scene parsing network
Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, and Jiaya Jia · 2017
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Coco-stuff: Thing and stuff classes in context
Holger Caesar, Jasper Uijlings, and Vittorio Ferrari · 2018
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Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs
Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L. Yuille · 2018
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Encoder-decoder with atrous separable convolution for semantic image segmentation
Liang-Chieh Chen, Yukun Zhu, George Papandreou, Florian Schroff, and Hartwig Adam · 2018
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Unified perceptual parsing for scene understanding
Tete Xiao, Yingcheng Liu, Bolei Zhou, Yuning Jiang, and Jian Sun · 2018
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Context encoding for semantic segmentation
Hang Zhang, Kristin Dana, Jianping Shi, Zhongyue Zhang, Xiaogang Wang, Ambrish Tyagi, and Amit Agrawal · 2018
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Gcnet: Non-local networks meet squeeze-excitation networks and beyond
Yue Cao, Jiarui Xu, Stephen Lin, Fangyun Wei, and Han Hu · 2019
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Auto-deeplab: Hierarchical neural architecture search for semantic image segmentation
Chenxi Liu, Liang-Chieh Chen, Florian Schroff, Hartwig Adam, Wei Hua, Alan Yuille, and Li Fei-Fei · 2019
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Semantic correlation promoted shape-variant context for segmentation
Henghui Ding, Xudong Jiang, Bing Shuai, Ai Qun Liu, and Gang Wang · 2019
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Acnet: Strengthening the kernel skeletons for powerful cnn via asymmetric convolution blocks
Xiaohan Ding, Yuchen Guo, Guiguang Ding, and Jungong Han · 2019
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Dual attention network for scene segmentation
Jun Fu, Jing Liu, Haijie Tian, Yong Li, Yongjun Bao, Zhiwei Fang, and Hanqing Lu · 2019
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Dynamic multi-scale filters for semantic segmentation
Junjun He, Zhongying Deng, and Yu Qiao · 2019
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Dsanet: Dual self-attention network for multivariate time series forecasting
Siteng Huang, Donglin Wang, Xuehan Wu, and Ao Tang · 2019
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Ccnet: Criss-cross attention for semantic segmentation
Zilong Huang, Xinggang Wang, Lichao Huang, Chang Huang, Yunchao Wei, and Wenyu Liu · 2019
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Panoptic feature pyramid networks
Alexander Kirillov, Ross Girshick, Kaiming He, and Piotr Dollár · 2019
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Expectation-maximization attention networks for semantic segmentation
Xia Li, Zhisheng Zhong, Jianlong Wu, Yibo Yang, Zhouchen Lin, and Hong Liu · 2019
Feature pyramid transformer
Dong Zhang, Hanwang Zhang, Jinhui Tang, Meng Wang, Xiansheng Hua, and Qianru Sun · 2020
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Masked-attention mask transformer for universal image segmentation
Bowen Cheng, Ishan Misra, Alexander G Schwing, Alexander Kirillov, and Rohit Girdhar · 2021
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Per-pixel classification is not all you need for semantic segmentation
Bowen Cheng, Alex Schwing, and Alexander Kirillov · 2021
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, and Neil Houlsby · 2021
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Mining contextual information beyond image for semantic segmentation
Zhenchao Jin, Tao Gong, Dongdong Yu, Qi Chu, Jian Wang, Changhu Wang, and Jie Shao · 2021
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Fast neural architecture search of compact semantic segmentation models via auxiliary cells
Vladimir Nekrasov, Hao Chen, Chunhua Shen, and Ian Reid · 2019
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Semantic understanding of scenes through the ade20k dataset
Bolei Zhou, Hang Zhao, Xavier Puig, Tete Xiao, Sanja Fidler, Adela Barriuso, and Antonio Torralba · 2019
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Asymmetric non-local neural networks for semantic segmentation
Zhen Zhu, Mengde Xu, Song Bai, Tengteng Huang, and Xiang Bai · 2019
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Tensor low-rank reconstruction for semantic segmentation
Wanli Chen, Xinge Zhu, Ruoqi Sun, Junjun He, Ruiyu Li, Xiaoyong Shen, and Bei Yu · 2020
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Deep multi-modal object detection and semantic segmentation for autonomous driving: Datasets, methods, and challenges
Di Feng, Christian Haase-Schütz, Lars Rosenbaum, Heinz Hertlein, Claudius Glaeser, Fabian Timm, Werner Wiesbeck, and Klaus Dietmayer · 2020
Cited alongside, same era.
Encoder-decoder with cascaded crfs for semantic segmentation
Jian Ji, Rui Shi, Sitong Li, Peng Chen, and Qiguang Miao · 2020
Cited alongside, same era.
Isnet: Integrate image-level and semantic-level context for semantic segmentation
Zhenchao Jin, Bin Liu, Qi Chu, and Nenghai Yu · 2021
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Swin transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
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Vision transformers for dense prediction
René Ranftl, Alexey Bochkovskiy, and Vladlen Koltun · 2021
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How to train your vit? data, augmentation, and regularization in vision transformers
Andreas Steiner, Alexander Kolesnikov, Xiaohua Zhai, Ross Wightman, Jakob Uszkoreit, and Lucas Beyer · 2021
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Segmenter: Transformer for semantic segmentation
Robin Strudel, Ricardo Garcia, Ivan Laptev, and Cordelia Schmid · 2021
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Stage-aware feature alignment network for real-time semantic segmentation of street scenes
Xi Weng, Yan Yan, Si Chen, Jing-Hao Xue, and Hanzi Wang · 2021
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Fully transformer networks for semantic image segmentation
Sitong Wu, Tianyi Wu, Fangjian Lin, Shengwei Tian, and Guodong Guo · 2021
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Segformer: Simple and efficient design for semantic segmentation with transformers
Enze Xie, Wenhai Wang, Zhiding Yu, Anima Anandkumar, Jose M Alvarez, and Ping Luo · 2021
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K-Net: Towards unified image segmentation
Wenwei Zhang, Jiangmiao Pang, Kai Chen, and Chen Change Loy · 2021
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Rethinking semantic segmentation from a sequence-to-sequence perspective with transformers
Sixiao Zheng, Jiachen Lu, Hengshuang Zhao, Xiatian Zhu, Zekun Luo, Yabiao Wang, Yanwei Fu, Jianfeng Feng, Tao Xiang, Philip H.S. Torr, and Li Zhang · 2021
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Learning statistical texture for semantic segmentation
Lanyun Zhu, Deyi Ji, Shiping Zhu, Weihao Gan, Wei Wu, and Junjie Yan · 2021
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All-higher-stages-in adaptive context aggregation for semantic edge detection
Qihan Bo, Wei Ma, Yu-Kun Lai, and Hongbin Zha · 2022
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Feature selective transformer for semantic image segmentation
Fangjian Lin, Tianyi Wu, Sitong Wu, Shengwei Tian, and Guodong Guo · 2022
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Gaussian dynamic convolution for efficient single-image segmentation
Xin Sun, Changrui Chen, Xiaorui Wang, Junyu Dong, Huiyu Zhou, and Sheng Chen · 2022
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