Bottom-Up Segmentation for Top-Down Detection

CVPR 2013 Sanja FidlerRoozbeh MottaghiAlan YuilleRaquel Urtasun

In this paper we are interested in how semantic segmentation can help object detection. Towards this goal, we propose a novel deformable part-based model which exploits region-based segmentation algorithms that compute candidate object regions by bottom-up clustering followed by ranking of those regions... (read more)

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