PaperCVPR 2016 · 2016
You Only Look Once: Unified, Real-Time Object Detection
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YOLOv1
Single-stage CNN object detector that frames detection as one regression problem from full-image pixels to a 7×7×30 tensor of grid-cell box offsets, objectness, and 20-class probabilities — trained end-to-end and inferring 98 boxes per image at 45 fps on a Titan X.
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2005Histograms of Oriented Gradients for Human DetectionDalal, Triggs2010Object Detection with Discriminatively Trained Part-Based ModelsFelzenszwalb, Girshick et al.2014Very Deep Convolutional Networks for Large-Scale Image RecognitionSimonyan, Zisserman2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal NetworksRen, He et al.2015Going deeper with convolutionsSzegedy, Liu et al.Built upon by · 0