You Only Look Once: Unified, Real-Time Object Detection

CVPR 2016
Pages: 779 - 788
Published: Jun 27, 2016
Abstract
We present YOLO, a new approach to object detection. Prior work on object detection repurposes classifiers to perform detection. Instead, we frame object detection as a regression problem to spatially separated bounding boxes and associated class probabilities. A single neural network predicts bounding boxes and class probabilities directly from full images in one evaluation. Since the whole detection pipeline is a single network, it can be...
Paper Details
Title
You Only Look Once: Unified, Real-Time Object Detection
Published Date
Jun 27, 2016
Journal
Pages
779 - 788
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