Learning to Segment Object Candidates

NeurIPS 2015 Pedro O. PinheiroRonan CollobertPiotr Dollar

Recent object detection systems rely on two critical steps: (1) a set of object proposals is predicted as efficiently as possible, and (2) this set of candidate proposals is then passed to an object classifier. Such approaches have been shown they can be fast, while achieving the state of the art in detection performance... (read more)

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