BING: Binarized Normed Gradients for Objectness Estimation at 300fpsMing-Ming Cheng1 Ziming Zhang2 Wen-Yan Lin3 Philip Torr1 1The University of Oxford 2Boston University 3Brookes Vision Group Abstract Training a generic objectness measure to produce a small set of candidate object windows, has been shown to speed up the classical sliding window object detection paradigm. We observe that generic objects with well-defined closed b
近似計算を導入した線形識別器の早期判定による高速な識別
