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

@article{Redmon2016YouOL,
  title={You Only Look Once: Unified, Real-Time Object Detection},
  author={Joseph Redmon and S. Divvala and Ross B. Girshick and A. Farhadi},
  journal={2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2016},
  pages={779-788}
}
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 optimized end-to-end directly on detection performance… Expand
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