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CANet: Co-attention network for RGB-D semantic segmentation

文献类型：期刊论文

作者Zhou, Hao2,3,5; Qi, Lu4; Huang, Hai5; Yang, Xu2,3; Wan, Zhaoliang5; Wen, Xianglong1
刊名PATTERN RECOGNITION
出版日期2022-04-01
卷号124页码:11
关键词RGB-D Multi -modal fusion Co-attention Semantic segmentation
ISSN号0031-3203
DOI10.1016/j.patcog.2021.108468
通讯作者Huang, Hai(haihus@163.com)
英文摘要Incorporating the depth (D) information to RGB images has proven the effectiveness and robustness in semantic segmentation. However, the fusion between them is not trivial due to their inherent physical meaning discrepancy, in which RGB represents RGB information but D depth information. In this paper, we propose a co-attention network (CANet) to build sound interaction between RGB and depth features. The key part in the CANet is the co-attention fusion part. It includes three modules. Specifically, the po-sition and channel co-attention fusion modules adaptively fuse RGB and depth features in spatial and channel dimensions. An additional fusion co-attention module further integrates the outputs of the posi-tion and channel co-attention fusion modules to obtain a more representative feature which is used for the final semantic segmentation. Extensive experiments witness the effectiveness of the CANet in fus-ing RGB and depth features, achieving state-of-the-art performance on two challenging RGB-D semantic segmentation datasets, i.e., NYUDv2 and SUN-RGBD. (c) 2021 Elsevier Ltd. All rights reserved.
WOS关键词FEATURES
资助项目National Natural Science Foundation (NSFC) of China[61633009] ; National Natural Science Foundation (NSFC) of China[61973301] ; National Natural Science Foundation (NSFC) of China[61972020] ; National Natural Science Foundation (NSFC) of China[51579053] ; National Natural Science Foundation (NSFC) of China[51779058] ; Beijing Science and Technology Plan Project[Z18110 0 0 08918018] ; National Key R&D Program of China[2016YFC0300801] ; National Key R&D Program of China[2017YFB1300202] ; National Key R&D Program of China[2020AAA0108902]
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:000736972200013
出版者ELSEVIER SCI LTD
资助机构National Natural Science Foundation (NSFC) of China ; Beijing Science and Technology Plan Project ; National Key R&D Program of China
源URL[http://ir.ia.ac.cn/handle/173211/47130]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_机器人应用与理论组
通讯作者Huang, Hai
作者单位1.Jihua Lab, Foshan, Peoples R China
2.Univ Chinese Acad Sci, Beijing, Peoples R China
3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China
4.Chinese Univ Hong Kong, Hong Kong, Peoples R China
5.Harbin Engn Univ, Natl Key Lab Sci & Technol Underwater Vehicle, Harbin, Peoples R China
推荐引用方式
GB/T 7714		 Zhou, Hao,Qi, Lu,Huang, Hai,et al. CANet: Co-attention network for RGB-D semantic segmentation[J]. PATTERN RECOGNITION,2022,124:11.
APA Zhou, Hao,Qi, Lu,Huang, Hai,Yang, Xu,Wan, Zhaoliang,&Wen, Xianglong.(2022).CANet: Co-attention network for RGB-D semantic segmentation.PATTERN RECOGNITION,124,11.
MLA Zhou, Hao,et al."CANet: Co-attention network for RGB-D semantic segmentation".PATTERN RECOGNITION 124(2022):11.

入库方式： OAI收割

来源：自动化研究所

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