Learning to Segment Object Candidates

@inproceedings{Pinheiro2015LearningTS,
  title={Learning to Segment Object Candidates},
  author={Pedro H. O. Pinheiro and Ronan Collobert and Piotr Doll{\'a}r},
  booktitle={NIPS},
  year={2015}
}
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. In this paper, we propose a new way to generate object proposals, introducing an approach based on a discriminative convolutional network. Our model is trained jointly with… CONTINUE READING
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