BING: Binarized normed gradients for objectness estimation at 300fps

• Main Authors: CHENG, Ming-Ming, LIU, Yun, LIN, Wen-yan, ZHANG, Ziming, ROSIN, Paul L., TORR, Philip H. S.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: visual attention; category agnostic proposals; object proposals; objectness; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/4716; https://ink.library.smu.edu.sg/context/sis_research/article/5719/viewcontent/ObjectnessBING.pdf
• Institution: Singapore Management University

Training a generic objectness measure to produce object proposals has recently become of significant interest. We observe that generic objects with well-defined closed boundaries can be detected by looking at the norm of gradients, with a suitable resizing of their corresponding image windows to a s...