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2018 | OriginalPaper | Chapter

A Fine-Grained Filtered Viewpoint Informed Keypoint Prediction from 2D Images

Authors : Qingnan Li, Ruimin Hu, Yixin Chen, Jingwen Yan, Jing Xiao

Published in: Advances in Multimedia Information Processing – PCM 2017

Publisher: Springer International Publishing

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Abstract

Viewpoint informed keypoint prediction from 2D images is an essential task in computer vision, which captures the fine details of rigid objects, however, the cases of ambiguous viewpoint predicted by the convolutional neural network, especially for two peaks of high confidence viewpoint proposals, may specify a set of erroneous keypoints. To address the above issue, we present multiscale convolutional neural networks and propose a filter to ensure high confidence viewpoint informed, which provides a global perspective for keypoint prediction. Leveraging the global precedence, we combine multiscale local appearance based keypoint likelihood with filtered viewpoint conditioned likelihood to induce a considerable performance gain. Experimentally, we show that our framework outperforms state-of-the-art methods on PASCAL 3D benchmark.

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Metadata
Title
A Fine-Grained Filtered Viewpoint Informed Keypoint Prediction from 2D Images
Authors
Qingnan Li
Ruimin Hu
Yixin Chen
Jingwen Yan
Jing Xiao
Copyright Year
2018
Book
Advances in Multimedia Information Processing – PCM 2017

Print ISBN: 978-3-319-77382-7

Electronic ISBN: 978-3-319-77383-4

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-77383-4_17