Instance Segmentation Evaluation
Instance Segmentation Evaluation is a technical methodology in computer vision that quantitatively assesses the accuracy of predicted object instances by distinguishing overlapping segmented regions through pixel-level and object-level correspondence with ground truth annotations.
227
Publications
17.4K
Citations
1K
Authors
373
Institutions
Publications per year
2017–2026
218
Parents
227
Zhaojin Huang, Lichao Huang, Yongchao Gong et al. · 2019 · 1.1K citations
SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentation
Weiyue Wang, Ronald Yu, Qiangui Huang et al. · 2018 · 592 citations
A Multi-Organ Nucleus Segmentation Challenge
Ruchika Verma, Deepak Anand, Yanning Zhou et al. · IEEE Transactions on Medical Imaging · 2019 · 544 citations · Full text
1–5 of 227
1K
6
h-index
4
h-index
4
h-index
4
h-index
4
h-index
1–5 of 1K
373

Chinese Academy of Sciences
Beijing, China
10 h-index
35 publications
2.5K citations
University of Chinese Academy of Sciences
Beijing, China
10 h-index
22 publications
1.7K citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
9 h-index
32 publications
6K citations
University of Science and Technology of China
Hefei, China
8 h-index
16 publications
1.8K citations
University of California, Berkeley
Berkeley, United States
7 h-index
11 publications
1.2K citations

Huazhong University of Science and Technology
Wuhan, China
6 h-index
19 publications
3.3K citations
Institute of Automation
Beijing, China
6 h-index
15 publications
852 citations
Tsinghua University
Beijing, China
5 h-index
20 publications
964 citations
1–8 of 373
Repository · 33 publications · 1.2K citations
18
h-index
Conference · 7 publications · 469 citations
7
h-index
7 publications · 476 citations
7
h-index
6 publications · 758 citations
6
h-index
6 publications · 192 citations
6
h-index
1–5