Subcategory-Aware Convolutional Neural Networks for Object Proposals and Detection (2016-04-16T00:00:00.000000Z)

TL;DR

A novel region proposal network that uses subcategory information to guide the proposal generating process, and a new detection network for joint detection and subcategory classification that achieves state of-the-art performance on both detection and pose estimation on commonly used benchmarks are introduced.

Abstract

In Convolutional Neural Network (CNN)-based object detection methods, region proposal becomes a bottleneck when objects exhibit significant scale variation, occlusion or truncation. In addition, these methods mainly focus on 2D object detection and cannot estimate detailed properties of objects. In this paper, we propose subcategory-aware CNNs for object detection. We introduce a novel region proposal network that uses subcategory information to guide the proposal generating process, and a new detection network for joint detection and subcategory classification. By using subcategories related to object pose, we achieve state of-the-art performance on both detection and pose estimation on commonly used benchmarks.

Authors

S. Savarese

31 papers

Yu Xiang

8 papers

Yuanqing Lin

2 papers

TL;DR

Abstract

Authors

References43 items

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