Computer Vision – ECCV 2016 Workshops

Amsterdam, The Netherlands, October 8-10 and 15-16, 2016, Proceedings, Part III

  • Hua Gang 
  • Jégou Hervé 
Conference proceedings ECCV 2016

DOI: 10.1007/978-3-319-49409-8

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9915)

Table of contents (75 papers)

  1. Front Matter
    Pages I-XXIII
  2. W04 – Brave New Ideas For Motion Representations (Continued)

    1. Front Matter
      Pages 1-2
    2. Back to Basics: Unsupervised Learning of Optical Flow via Brightness Constancy and Motion Smoothness
      Jason J. Yu, Adam W. Harley, Konstantinos G. Derpanis
      Pages 3-10
    3. Human Action Recognition Without Human
      Yun He, Soma Shirakabe, Yutaka Satoh, Hirokatsu Kataoka
      Pages 11-17
    4. Motion Representation with Acceleration Images
      Hirokatsu Kataoka, Yun He, Soma Shirakabe, Yutaka Satoh
      Pages 18-24
    5. Segmentation Free Object Discovery in Video
      Giovanni Cuffaro, Federico Becattini, Claudio Baecchi, Lorenzo Seidenari, Alberto Del Bimbo
      Pages 25-31
    6. Human Pose Estimation in Space and Time Using 3D CNN
      Agne Grinciunaite, Amogh Gudi, Emrah Tasli, Marten den Uyl
      Pages 32-39
    7. Temporal Convolutional Networks: A Unified Approach to Action Segmentation
      Colin Lea, René Vidal, Austin Reiter, Gregory D. Hager
      Pages 47-54
    8. Making a Case for Learning Motion Representations with Phase
      S. L. Pintea, J. C. van Gemert
      Pages 55-64
  3. W06 – Geometry Meets Deep Learning

    1. Front Matter
      Pages 65-66
    2. gvnn: Neural Network Library for Geometric Computer Vision
      Ankur Handa, Michael Bloesch, Viorica Pătrăucean, Simon Stent, John McCormac, Andrew Davison
      Pages 67-82
    3. On-Line Large Scale Semantic Fusion
      Tommaso Cavallari, Luigi Di Stefano
      Pages 83-99
    4. Learning Covariant Feature Detectors
      Karel Lenc, Andrea Vedaldi
      Pages 100-117
    5. Scene Segmentation Driven by Deep Learning and Surface Fitting
      Ludovico Minto, Giampaolo Pagnutti, Pietro Zanuttigh
      Pages 118-132
    6. Improving Constrained Bundle Adjustment Through Semantic Scene Labeling
      Achkan Salehi, Vincent Gay-Bellile, Steve Bourgeois, Frédéric Chausse
      Pages 133-142
    7. A CNN Cascade for Landmark Guided Semantic Part Segmentation
      Aaron S. Jackson, Michel Valstar, Georgios Tzimiropoulos
      Pages 143-155
    8. Overcoming Occlusion with Inverse Graphics
      Pol Moreno, Christopher K. I. Williams, Charlie Nash, Pushmeet Kohli
      Pages 170-185
    9. Deep Kinematic Pose Regression
      Xingyi Zhou, Xiao Sun, Wei Zhang, Shuang Liang, Yichen Wei
      Pages 186-201

Other volumes

  1. Computer Vision – ECCV 2016
    14th European Conference, Amsterdam, The Netherlands, October 11–14, 2016, Proceedings, Part I
  2. Computer Vision – ECCV 2016
    14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part II
  3. Computer Vision – ECCV 2016
    14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part III
  4. Computer Vision – ECCV 2016
    14th European Conference, Amsterdam, The Netherlands, October 11–14, 2016, Proceedings, Part IV
  5. Computer Vision – ECCV 2016
    14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part V
  6. Computer Vision – ECCV 2016
    14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part VI
  7. Computer Vision – ECCV 2016
    14th European Conference, Amsterdam, The Netherlands, October 11–14, 2016, Proceedings, Part VII
  8. Computer Vision – ECCV 2016
    14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part VIII
  9. Computer Vision – ECCV 2016 Workshops
    Amsterdam, The Netherlands, October 8-10 and 15-16, 2016, Proceedings, Part I
  10. Computer Vision – ECCV 2016 Workshops
    Amsterdam, The Netherlands, October 8-10 and 15-16, 2016, Proceedings, Part II
  11. Computer Vision – ECCV 2016 Workshops
    Amsterdam, The Netherlands, October 8-10 and 15-16, 2016, Proceedings, Part III

About these proceedings

Introduction

The three-volume set LNCS 9913, LNCS 9914, and LNCS 9915 comprises the refereed proceedings of the Workshops that took place in conjunction with the 14th European Conference on Computer Vision, ECCV 2016, held in Amsterdam, The Netherlands, in October 2016.

The three-volume set LNCS 9913, LNCS 9914, and LNCS 9915 comprises the refereed proceedings of the Workshops that took place in conjunction with the 14th European Conference on Computer Vision, ECCV 2016, held in Amsterdam, The Netherlands, in October 2016.

27 workshops from 44 workshops proposals were selected for inclusion in the proceedings. These address the following themes: Datasets and Performance Analysis in Early Vision; Visual Analysis of Sketches; Biological and Artificial Vision; Brave New Ideas for Motion Representations; Joint ImageNet and MS COCO Visual Recognition Challenge; Geometry Meets Deep Learning; Action and Anticipation for Visual Learning; Computer Vision for Road Scene Understanding and Autonomous Driving; Challenge on Automatic Personality Analysis; BioImage Computing; Benchmarking Multi-Target Tracking: MOTChallenge; Assistive Computer Vision and Robotics; Transferring and Adapting Source Knowledge in Computer Vision; Recovering 6D Object Pose; Robust Reading; 3D Face Alignment in the Wild and Challenge; Egocentric Perception, Interaction and Computing; Local Features: State of the Art, Open Problems and Performance Evaluation; Crowd Understanding; Video Segmentation; The Visual Object Tracking Challenge Workshop; Web-scale Vision and Social Media; Computer Vision for Audio-visual Media; Computer VISion for ART Analysis; Virtual/Augmented Reality for Visual Artificial Intelligence; Joint Workshop on Storytelling with Images and Videos and Large Scale Movie Description and Understanding Challenge.

Keywords

computer vision digital heritage image database semantic embedding topic modeling active safety systems adaptive learning context-based analysis deep learning dimensionality reduction face recognition GPU mobile applications multimodal embedding neural networks scene understanding semi-supervised learning text detection video segmentation wearable devices

Editors and affiliations

  • Hua Gang 
    • 1
  • Jégou Hervé 
    • 2
  1. 1.Microsoft Research AsiaBeijingChina
  2. 2.Facebook AI Research (FAIR)Menlo ParkUSA

Bibliographic information

  • Copyright Information Springer International Publishing Switzerland 2016
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-49408-1
  • Online ISBN 978-3-319-49409-8
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349