Panoptic-DeepLab

Generalizing the hough transform to detect arbitrary shapes

Dana H Ballard · 1981

Earlier work this paper cites.

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

Earlier work this paper cites.

The mapillary vistas dataset for semantic understanding of street scenes

Gerhard Neuhold, Tobias Ollmann, Samuel Rota Bulò, and Peter Kontschieder · 2017

Earlier work this paper cites.

Encoder-decoder with atrous separable convolution for semantic image segmentation

Liang-Chieh Chen, Yukun Zhu, George Papandreou, Florian Schroff, and Hartwig Adam · 2018

Earlier work this paper cites.

Multi-task learning using uncertainty to weigh losses for scene geometry and semantics

Alex Kendall, Yarin Gal, and Roberto Cipolla · 2018

Earlier work this paper cites.

Learning to fuse things and stuff

Original

Jie Li, Allan Raventos, Arjun Bhargava, Takaaki Tagawa, and Adrien Gaidon · 2018

Earlier work this paper cites.

Path aggregation network for instance segmentation

Shu Liu, Lu Qi, Haifang Qin, Jianping Shi, and Jiaya Jia · 2018

Cited alongside, same era.

Ssap: Single-shot instance segmentation with affinity pyramid

Naiyu Gao, Yanhu Shan, Yupei Wang, Xin Zhao, Yinan Yu, Ming Yang, and Kaiqi Huang · 2019

Cited alongside, same era.

Panoptic feature pyramid networks

Alexander Kirillov, Ross Girshick, Kaiming He, and Piotr Dollár · 2019

Cited alongside, same era.

Panoptic segmentation

Alexander Kirillov, Kaiming He, Ross Girshick, Carsten Rother, and Piotr Dollár · 2019

Cited alongside, same era.

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

Cited alongside, same era.

Seamless scene segmentation

Lorenzo Porzi, Samuel Rota Bulò, Aleksander Colovic, and Peter Kontschieder · 2019

Cited alongside, same era.

Adaptis: Adaptive instance selection network

Konstantin Sofiiuk, Olga Barinova, and Anton Konushin · 2019

Closest in time.

Deep high-resolution representation learning for visual recognition

Original

Jingdong Wang, Ke Sun, Tianheng Cheng, Borui Jiang, Chaorui Deng, Yang Zhao, Dong Liu, Yadong Mu, Mingkui Tan, Xinggang Wang, Wenyu Liu, and Bin Xiao · 2019

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Upsnet: A unified panoptic segmentation network

Yuwen Xiong, Renjie Liao, Hengshuang Zhao, Rui Hu, Min Bai, Ersin Yumer, and Raquel Urtasun · 2019

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Deeperlab: Single-shot image parser

Original

Tien-Ju Yang, Maxwell D Collins, Yukun Zhu, Jyh-Jing Hwang, Ting Liu, Xiao Zhang, Vivienne Sze, George Papandreou, and Liang-Chieh Chen · 2019

Closest in time.

Improving semantic segmentation via video propagation and label relaxation

Yi Zhu, Karan Sapra, Fitsum A Reda, Kevin J Shih, Shawn Newsam, Andrew Tao, and Bryan Catanzaro · 2019

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