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Titlebook: Computer Vision -- ACCV 2014; 12th Asian Conferenc Daniel Cremers,Ian Reid,Ming-Hsuan Yang Conference proceedings 2015 Springer Internation

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书目名称Computer Vision -- ACCV 2014
副标题12th Asian Conferenc
编辑Daniel Cremers,Ian Reid,Ming-Hsuan Yang
视频video
概述Includes supplementary material:
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Computer Vision -- ACCV 2014; 12th Asian Conferenc Daniel Cremers,Ian Reid,Ming-Hsuan Yang Conference proceedings 2015 Springer Internation
描述The five-volume set LNCS 9003--9007 constitutes the thoroughly refereed post-conference proceedings of the 12th Asian Conference on Computer Vision, ACCV 2014, held in Singapore, Singapore, in November 2014. The total of 227 contributions presented in these volumes was carefully reviewed and selected from 814 submissions. The papers are organized in topical sections on recognition; 3D vision; low-level vision and features; segmentation; face and gesture, tracking; stereo, physics, video and events; and poster sessions 1-3.
出版日期Conference proceedings 2015
关键词Action recognition; Aerial images; Camera calibration; City-scale; Data Mining; Differential constraints;
版次1
doihttps://doi.org/10.1007/978-3-319-16817-3
isbn_softcover978-3-319-16816-6
isbn_ebook978-3-319-16817-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing Switzerland 2015
The information of publication is updating

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EPML: Expanded Parts Based Metric Learning for Occlusion Robust Face Verificationons at the right locations and scales, for identity based matching of face images. It performs well in the presence of occlusions, by avoiding the occluded regions and selecting the next best visible regions. We show quantitatively, by experiments on the standard benchmark dataset Labeled Faces in t
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Beyond Procedural Facade Parsing: Bidirectional Alignment via Linear Programmingthe procedural space of shapes derived from a grammar. Instead we formulate parsing as a linear binary program which we solve using Dual Decomposition. The algorithm produces plausible approximations of globally optimal segmentations without grammar sampling. It yields state-of-the-art performance o
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A+: Adjusted Anchored Neighborhood Regression for Fast Super-Resolutiono recently proposed methods, Anchored Neighborhood Regression (ANR) and Simple Functions (SF), provide state-of-the-art quality performance. Moreover, ANR is among the fastest known super-resolution methods. ANR learns sparse dictionaries and regressors anchored to the dictionary atoms. SF relies on
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