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Computer Science > Computer Vision and Pattern Recognition

Title: Learning Region Features for Object Detection

Abstract: While most steps in the modern object detection methods are learnable, the region feature extraction step remains largely hand-crafted, featured by RoI pooling methods. This work proposes a general viewpoint that unifies existing region feature extraction methods and a novel method that is end-to-end learnable. The proposed method removes most heuristic choices and outperforms its RoI pooling counterparts. It moves further towards fully learnable object detection.
Subjects: Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:1803.07066 [cs.CV]
  (or arXiv:1803.07066v1 [cs.CV] for this version)

Submission history

From: Jifeng Dai [view email]
[v1] Mon, 19 Mar 2018 17:58:50 GMT (1249kb,D)