Boundary-aware Segmentation
Boundary-Aware Segmentation is a semantic segmentation method that enhances pixel-level classification accuracy by explicitly modeling object boundary information to distinguish between adjacent instances and improve segmentation coherence.
262
Publications
33.1K
Citations
1.1K
Authors
390
Institutions
Publications per year
2017–2026
190
262
Large Kernel Matters — Improve Semantic Segmentation by Global Convolutional Network
Chao Peng, Xiangyu Zhang, Gang Yu et al. · 2017 · 1.7K citations
BASNet: Boundary-Aware Salient Object Detection
Xuebin Qin, Zichen Zhang, Chenyang Huang et al. · 2019 · 1.6K citations
BING: Binarized Normed Gradients for Objectness Estimation at 300fps
Ming‐Ming Cheng, Ziming Zhang, Wen-Yan Lin et al. · 2014 · 1.1K citations · Full text
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390

Chinese Academy of Sciences
Beijing, China
12 h-index
35 publications
1.8K citations
University of Chinese Academy of Sciences
Beijing, China
10 h-index
29 publications
1.9K citations

Zhejiang University
Hangzhou, China
7 h-index
23 publications
806 citations

Huazhong University of Science and Technology
Wuhan, China
7 h-index
21 publications
3.3K citations
Tsinghua University
Beijing, China
6 h-index
20 publications
4.2K citations

Peking University
Beijing, China
6 h-index
11 publications
1.5K citations

University of Electronic Science and Technology of China
Chengdu, China
6 h-index
24 publications
915 citations
Wuhan University
Wuhan, China
6 h-index
21 publications
1.6K citations
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Repository · 17 publications · 5.2K citations
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12 publications · 881 citations
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9 publications · 594 citations
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7 publications · 216 citations
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7 publications · 354 citations
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