Objectness Detection
Objectness Detection is a computational framework in computer vision that identifies image regions likely to contain meaningful objects, distinguished from other detection approaches by focusing on proposing object-like regions without requiring prior knowledge of specific object categories.
137
Publications
84.4K
Citations
492
Authors
186
Institutions
Publications per year
2017–2026
83
Parents
137
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Shaoqing Ren, Kaiming He, Ross Girshick et al. · arXiv (Cornell University) · 2015 · 18.2K citations · Full text
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
Bogdan Alexe, Thomas Deselaers, Vittorio Ferrari · 2010 · 804 citations
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186
Tsinghua University
Beijing, China
7 h-index
21 publications
3.2K citations

Beihang University
Beijing, China
6 h-index
20 publications
902 citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
6 h-index
16 publications
712 citations

Chinese Academy of Sciences
Beijing, China
6 h-index
17 publications
617 citations
University of Oxford
Oxford, United Kingdom
5 h-index
6 publications
2.5K citations

Australian National University
Canberra, Australia
5 h-index
11 publications
992 citations
Google (United States)
Mountain View, United States
5 h-index
9 publications
686 citations

Northwestern Polytechnical University
Xi'an, China
4 h-index
16 publications
2.7K citations
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Repository · 19 publications · 19K citations
13
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8 publications · 427 citations
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TPAMI · 5 publications · 55.6K citations
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4 publications · 272 citations
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5 publications · 324 citations
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