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Titlebook: Computer Vision – ECCV 2016; 14th European Confer Bastian Leibe,Jiri Matas,Max Welling Conference proceedings 2016 Springer International P

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书目名称Computer Vision – ECCV 2016
副标题14th European Confer
编辑Bastian Leibe,Jiri Matas,Max Welling
视频video
概述Includes supplementary material:
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Computer Vision – ECCV 2016; 14th European Confer Bastian Leibe,Jiri Matas,Max Welling Conference proceedings 2016 Springer International P
描述.The eight-volume set comprising LNCS volumes 9905-9912 constitutes the refereed proceedings of the 14th European Conference on Computer Vision, ECCV 2016, held in Amsterdam, The Netherlands, in October 2016. . The 415 revised papers presented were carefully reviewed and selected from 1480 submissions. The papers cover all aspects of computer vision and pattern recognition such as 3D computer vision;  computational photography, sensing and display; face and gesture; low-level vision and image processing; motion and tracking; optimization methods; physics-based vision, photometry and shape-from-X; recognition: detection, categorization, indexing, matching; segmentation, grouping and shape representation; statistical methods and learning; video: events, activities and surveillance; applications. They are organized in topical sections on detection, recognition and retrieval; scene understanding; optimization; image and video processing; learning; action, activity and tracking; 3D; and 9 poster sessions..
出版日期Conference proceedings 2016
关键词computational photography; image classification; particle swarm optimization; pattern mining; semantic c
版次1
doihttps://doi.org/10.1007/978-3-319-46466-4
isbn_softcover978-3-319-46465-7
isbn_ebook978-3-319-46466-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing AG 2016
The information of publication is updating

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Epidermal cellular organizationaccomplished using an adaptive query strategy derived from probing the properties of the graph in the frequency space. To demonstrate the benefits that this framework can provide, we present experimental evaluations on two independent neuroimaging studies and show that our proposed method can reliab
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D. Allgüwer,P Matter,SM Perren,T Rüedird-Shah functional, for which we derive an effective optimization strategy. Our experiments evidence that our approach can accurately fill the large holes in the input depth maps, segment the different kinds of objects in the scene, and hallucinate the depth and semantics behind the foreground objec
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Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzlesnd validation set of Pascal VOC 2007 for object detection (via fast RCNN) and classification. These features outperform all current unsupervised features with . for detection and . for classification, and reduce the gap with supervised learning (. and . respectively).
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COCO Attributes: Attributes for People, Animals, and Objectsnstrate that our efficiently labeled training data can be used to produce classifiers of similar discriminative ability as classifiers created using exhaustively labeled ground truth. Finally, we provide baseline performance analysis for object attribute recognition.
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Temporally Robust Global Motion Compensation by Keypoint-Based Congealing matching local keypoints of each frame. A joint alignment of these frames is formulated as a novel keypoint-based congealing problem, where the transformation of each frame is updated iteratively, such that the spatial coordinates for the start and end points of matched keypoints are identical. Exp
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Adaptive Signal Recovery on Graphs via Harmonic Analysis for Experimental Design in Neuroimagingaccomplished using an adaptive query strategy derived from probing the properties of the graph in the frequency space. To demonstrate the benefits that this framework can provide, we present experimental evaluations on two independent neuroimaging studies and show that our proposed method can reliab
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