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Computer Vision – ECCV 2016

14th European Conference, Amsterdam, The Netherlands, October 11–14, 2016, Proceedings, Part I

  • Conference proceedings
  • © 2016

Overview

Editors:
  1. Bastian Leibe

    1. RWTH Aachen , Aachen, Germany

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  2. Jiri Matas

    1. Czech Technical University , Prague 2, Czech Republic

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  3. Nicu Sebe

    1. University of Trento , Povo - Trento, Italy

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  4. Max Welling

    1. University of Amsterdam , Amsterdam, The Netherlands

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 9905)

Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)

Included in the following conference series:

Conference proceedings info: ECCV 2016.

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About this book

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.

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Table of contents (51 papers)

  1. Front Matter

    Pages I-XXIX
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  2. Detection, Recognition and Retrieval

    1. Front Matter

      Pages 1-1
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    2. CNN Image Retrieval Learns from BoW: Unsupervised Fine-Tuning with Hard Examples

      • Filip Radenović, Giorgos Tolias, Ondřej Chum
      Pages 3-20

    3. SSD: Single Shot MultiBox Detector

      • Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu et al.
      Pages 21-37

    4. A Recurrent Encoder-Decoder Network for Sequential Face Alignment

      • Xi Peng, Rogerio S. Feris, Xiaoyu Wang, Dimitris N. Metaxas
      Pages 38-56

    5. Robust Facial Landmark Detection via Recurrent Attentive-Refinement Networks

      • Shengtao Xiao, Jiashi Feng, Junliang Xing, Hanjiang Lai, Shuicheng Yan, Ashraf Kassim
      Pages 57-72

  3. Poster Session 1

    1. Front Matter

      Pages 73-73
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    2. Learning to Refine Object Segments

      • Pedro O. Pinheiro, Tsung-Yi Lin, Ronan Collobert, Piotr Dollár
      Pages 75-91

    3. Deep Automatic Portrait Matting

      • Xiaoyong Shen, Xin Tao, Hongyun Gao, Chao Zhou, Jiaya Jia
      Pages 92-107

    4. Segmentation from Natural Language Expressions

      • Ronghang Hu, Marcus Rohrbach, Trevor Darrell
      Pages 108-124

    5. Semantic Object Parsing with Graph LSTM

      • Xiaodan Liang, Xiaohui Shen, Jiashi Feng, Liang Lin, Shuicheng Yan
      Pages 125-143

    6. SSHMT: Semi-supervised Hierarchical Merge Tree for Electron Microscopy Image Segmentation

      • Ting Liu, Miaomiao Zhang, Mehran Javanmardi, Nisha Ramesh, Tolga Tasdizen
      Pages 144-159

    7. Towards Viewpoint Invariant 3D Human Pose Estimation

      • Albert Haque, Boya Peng, Zelun Luo, Alexandre Alahi, Serena Yeung, Li Fei-Fei
      Pages 160-177

    8. Person Re-Identification by Unsupervised \(\ell _1\) Graph Learning

      • Elyor Kodirov, Tao Xiang, Zhenyong Fu, Shaogang Gong
      Pages 178-195

    9. Deep Learning the City: Quantifying Urban Perception at a Global Scale

      • Abhimanyu Dubey, Nikhil Naik, Devi Parikh, Ramesh Raskar, César A. Hidalgo
      Pages 196-212

    10. 4D Match Trees for Non-rigid Surface Alignment

      • Armin Mustafa, Hansung Kim, Adrian Hilton
      Pages 213-229

    11. Eigen Appearance Maps of Dynamic Shapes

      • Adnane Boukhayma, Vagia Tsiminaki, Jean-Sébastien Franco, Edmond Boyer
      Pages 230-245

    12. Learnable Histogram: Statistical Context Features for Deep Neural Networks

      • Zhe Wang, Hongsheng Li, Wanli Ouyang, Xiaogang Wang
      Pages 246-262

    13. Pedestrian Behavior Understanding and Prediction with Deep Neural Networks

      • Shuai Yi, Hongsheng Li, Xiaogang Wang
      Pages 263-279

    14. Real-Time RGB-D Activity Prediction by Soft Regression

      • Jian-Fang Hu, Wei-Shi Zheng, Lianyang Ma, Gang Wang, Jianhuang Lai
      Pages 280-296
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Other volumes

  1. Computer Vision – ECCV 2016

  2. Computer Vision – ECCV 2016

  3. Computer Vision – ECCV 2016

  4. Computer Vision – ECCV 2016

  5. Computer Vision – ECCV 2016

  6. Computer Vision – ECCV 2016

  7. Computer Vision – ECCV 2016

  8. Computer Vision – ECCV 2016

  9. Computer Vision – ECCV 2016 Workshops

  10. Computer Vision – ECCV 2016 Workshops

  11. Computer Vision – ECCV 2016 Workshops

Editors and Affiliations

  • RWTH Aachen , Aachen, Germany

    Bastian Leibe

  • Czech Technical University , Prague 2, Czech Republic

    Jiri Matas

  • University of Trento , Povo - Trento, Italy

    Nicu Sebe

  • University of Amsterdam , Amsterdam, The Netherlands

    Max Welling

Bibliographic Information

  • Book Title: Computer Vision – ECCV 2016

  • Book Subtitle: 14th European Conference, Amsterdam, The Netherlands, October 11–14, 2016, Proceedings, Part I

  • Editors: Bastian Leibe, Jiri Matas, Nicu Sebe, Max Welling

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-319-46448-0

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer International Publishing AG 2016

  • Softcover ISBN: 978-3-319-46447-3Published: 17 September 2016

  • eBook ISBN: 978-3-319-46448-0Published: 16 September 2016

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XXIX, 873

  • Number of Illustrations: 330 b/w illustrations

  • Topics: Image Processing and Computer Vision, Pattern Recognition, Artificial Intelligence, Computer Graphics

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