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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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發(fā)表于 2025-3-21 19:41:00 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Computer Vision – ECCV 2016
副標(biāo)題14th European Confer
編輯Bastian Leibe,Jiri Matas,Max Welling
視頻videohttp://file.papertrans.cn/235/234178/234178.mp4
概述Includes supplementary material:
叢書名稱Lecture Notes in Computer Science
圖書封面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
關(guān)鍵詞computational photography; image classification; particle swarm optimization; pattern mining; semantic c
版次1
doihttps://doi.org/10.1007/978-3-319-46487-9
isbn_softcover978-3-319-46486-2
isbn_ebook978-3-319-46487-9Series 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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Faceless Person Recognition: Privacy Implications in Social Medias works contributes to the understanding of privacy implications of such data sharing by analysing how well people are recognisable in social media data. To facilitate a systematic study we define a number of scenarios considering factors such as how many heads of a person are tagged and if those he
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Segmental Spatiotemporal CNNs for Fine-Grained Action Segmentationskill evaluation. However, despite substantial recent progress in large-scale action classification, the performance of state-of-the-art fine-grained action recognition approaches remains low. We propose a model for action segmentation which combines low-level spatiotemporal features with a high-lev
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Evaluation of LBP and Deep Texture Descriptors with a New Robustness Benchmarktistage convolutional networks and deep learning have also emerged. In different papers the performance comparison of the proposed methods to earlier approaches is mainly done with some well-known texture datasets, with differing classifiers and testing protocols, and often not using the best sets o
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A 4D Light-Field Dataset and CNN Architectures for Material Recognition4D light-field. Our dataset contains 12 material categories, each with 100 images taken with a Lytro Illum, from which we extract about 30,000 patches in?total. To the best of our knowledge, this is the first mid-size dataset for light-field images. Our main goal is to investigate whether the additi
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All-Around Depth from Small Motion with a Spherical Panoramic Camerar vision. For capturing full 360 degree panoramas in a single shot, the Spherical Panoramic Camera (SPC) are gaining in popularity. However, estimating depth from a SPC remains a challenging problem. In this paper, we propose a practical method that generates all-around dense depth map using a narro
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