Fetching the paper…
Reading the bibliography…
We present a novel boundary-aware loss term for semantic segmentation using an inverse-transformation network, which efficiently learns the degree of parametric transformations between estimated and target boundaries.
A computational approach to edge detection
John Canny · 1986
Earlier work this paper cites.
Minimization on the lie group so (3) and related manifolds
Camillo J Taylor and David J Kriegman · 1994
Earlier work this paper cites.
Learning to detect natural image boundaries using local brightness, color, and texture cues
D. R. Martin, C. C. Fowlkes, and J. Malik · 2004
Earlier work this paper cites.
Learning on lie groups for invariant detection and tracking
O. Tuzel, F. Porikli, and P. Meer · 2008
Earlier work this paper cites.
Efficient inference in fully connected CRFs with Gaussian edge potentials
Philipp Krähenbühl and Vladlen Koltun · 2011
Earlier work this paper cites.
Indoor segmentation and support inference from rgbd images
Nathan Silberman, Derek Hoiem, Pushmeet Kohli, and Rob Fergus · 2012
Earlier work this paper cites.
The pascal visual object classes challenge: A retrospective
Mark Everingham, S. Eslami, Luc Van Gool, Christopher Williams, John Winn, and Andrew Zisserman · 2014
Earlier work this paper cites.
Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Earlier work this paper cites.
Spatial transformer networks
Max Jaderberg, Karen Simonyan, Andrew Zisserman, and Koray Kavukcuoglu · 2015
Earlier work this paper cites.
Fully convolutional networks for semantic segmentation
Jonathan Long, Evan Shelhamer, and Trevor Darrell · 2015
Earlier work this paper cites.
Semantic segmentation with boundary neural fields
Gedas Bertasius, Jianbo Shi, and Lorenzo Torresani · 2016
Earlier work this paper cites.
Semantic image segmentation with task-specific edge detection using cnns and a discriminatively trained domain transform
Liang-Chieh Chen, Jonathan T Barron, George Papandreou, Kevin Murphy, and Alan L Yuille · 2016
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.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Pushing the boundaries of boundary detection using deep learning
Iasonas Kokkinos · 2016
Earlier work this paper cites.
Wide residual networks
Sergey Zagoruyko and Nikos Komodakis · 2016
Earlier work this paper cites.
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 · 2017
Earlier work this paper cites.
Fusionnet: Edge aware deep convolutional networks for semantic segmentation of remote sensing harbor images
Dongcai Cheng, Gaofeng Meng, Shiming Xiang, and Chunhong Pan · 2017
Earlier work this paper cites.
Blitznet: A real-time deep network for scene understanding
Nikita Dvornik, Konstantin Shmelkov, Julien Mairal, and Cordelia Schmid · 2017
Cited alongside, same era.
Ubernet: Training a universal convolutional neural network for low-, mid-, and high-level vision using diverse datasets and limited memory
Iasonas Kokkinos · 2017
Cited alongside, same era.
Refinenet: Multi-path refinement networks for high-resolution semantic segmentation
Guosheng Lin, Anton Milan, Chunhua Shen, and Ian Reid · 2017
Cited alongside, same era.
Learning affinity via spatial propagation networks
Sifei Liu, Shalini De Mello, Jinwei Gu, Guangyu Zhong, Ming-Hsuan Yang, and Jan Kautz · 2017
Cited alongside, same era.
The mapillary vistas dataset for semantic understanding of street scenes
G. Neuhold, T. Ollmann, S. R. Bulò, and P. Kontschieder · 2017
Cited alongside, same era.
High-resolution representations for labeling pixels and regions
Ke Sun, Yang Zhao, Borui Jiang, Tianheng Cheng, Bin Xiao, Dong Liu, Yadong Mu, Xinggang Wang, Wenyu Liu, and Jingdong Wang · 2019
Later among the works it cites.
Gated-scnn: Gated shape cnns for semantic segmentation
Towaki Takikawa, David Acuna, Varun Jampani, and Sanja Fidler · 2019
Later among the works it cites.
Aet vs. aed: Unsupervised representation learning by auto-encoding transformations rather than data
Liheng Zhang, Guo-Jun Qi, Liqiang Wang, and Jiebo Luo · 2019
Later among the works it cites.
Pattern-affinitive propagation across depth, surface normal and semantic segmentation
Zhenyu Zhang, Zhen Cui, Chunyan Xu, Yan Yan, Nicu Sebe, and Jian Yang · 2019
Later among the works it cites.
Naive-student: Leveraging semi-supervised learning in video sequences for urban scene segmentation
Liang-Chieh Chen, Raphael Gontijo Lopes, Bowen Cheng, Maxwell D. Collins, Ekin D. Cubuk, Barret Zoph, Hartwig Adam, and Jonathon Shlens · 2020
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Chao Peng, Xiangyu Zhang, Gang Yu, Guiming Luo, and Jian Sun · 2017
Cited alongside, same era.
Pyramid scene parsing network
Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, and Jiaya Jia · 2017
Cited alongside, same era.
Encoder-decoder with atrous separable convolution for semantic image segmentation
Liang-Chieh Chen, Yukun Zhu, George Papandreou, Florian Schroff, and Hartwig Adam · 2018
Cited alongside, same era.
Context contrasted feature and gated multi-scale aggregation for scene segmentation
Henghui Ding, Xudong Jiang, Bing Shuai, Ai Qun Liu, and Gang Wang · 2018
Cited alongside, same era.
Squeeze-and-excitation networks
Jie Hu, Li Shen, and Gang Sun · 2018
Cited alongside, same era.
Recurrent scene parsing with perspective understanding in the loop
Shu Kong and Charless C Fowlkes · 2018
Cited alongside, same era.
Weighted hausdorff distance: A loss function for object localization
Javier Ribera, David Güera, Yuhao Chen, and Edward J. Delp · 2018
Cited alongside, same era.
Later among the works it cites.
Cascadepsp: Toward class-agnostic and very high-resolution segmentation via global and local refinement
Ho Kei Cheng, Jihoon Chung, Yu-Wing Tai, and Chi-Keung Tang · 2020
Later among the works it cites.
Towards a deeper understanding of adversarial losses under a discriminative adversarial network setting, 2020
Hao-Wen Dong and Yi-Hsuan Yang · 2020
Later among the works it cites.
Temporally distributed networks for fast video semantic segmentation
Ping Hu, Fabian Caba, Oliver Wang, Zhe Lin, Stan Sclaroff, and Federico Perazzi · 2020
Later among the works it cites.
Pointrend: Image segmentation as rendering
Alexander Kirillov, Yuxin Wu, Kaiming He, and Ross Girshick · 2020
Later among the works it cites.
Hierarchical multi-scale attention for semantic segmentation
Andrew Tao, Karan Sapra, and Bryan Catanzaro · 2020
Later among the works it cites.
Multi-task learning for dense prediction tasks: A survey, 2020
Simon Vandenhende, Stamatios Georgoulis, Wouter Van Gansbeke, Marc Proesmans, Dengxin Dai, and Luc Van Gool · 2020
Later among the works it cites.
Mti-net: Multi-scale task interaction networks for multi-task learning
Simon Vandenhende, Stamatios Georgoulis, and Luc Van Gool · 2020
Later among the works it cites.
Deep high-resolution representation learning for visual recognition
Jingdong Wang, Ke Sun, Tianheng Cheng, Borui Jiang, Chaorui Deng, Yang Zhao, Dong Liu, Yadong Mu, Mingkui Tan, Xinggang Wang, et al · 2020
Later among the works it cites.
Deep high-resolution representation learning for visual recognition, 2020
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 · 2020
Later among the works it cites.
Malleable 2.5d convolution: Learning receptive fields along the depth-axis for rgb-d scene parsing, 2020
Yajie Xing, Jingbo Wang, and Gang Zeng · 2020
Later among the works it cites.
Object-contextual representations for semantic segmentation, 2020
Yuhui Yuan, Xilin Chen, and Jingdong Wang · 2020
Later among the works it cites.
Segfix: Model-agnostic boundary refinement for segmentation
Yuhui Yuan, Jingyi Xie, Xilin Chen, and Jingdong Wang · 2020
Later among the works it cites.