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Computer Vision – ECCV 2018

15th European Conference, Munich, Germany, September 8-14, 2018, Proceedings, Part XV

  • Vittorio Ferrari
  • Martial Hebert
  • Cristian Sminchisescu
  • Yair Weiss
Conference proceedings ECCV 2018

Part of the Lecture Notes in Computer Science book series (LNCS, volume 11219)

Also part of the Image Processing, Computer Vision, Pattern Recognition, and Graphics book sub series (LNIP, volume 11219)

Table of contents

  1. Front Matter
    Pages I-XXXI
    PDF

  2. Poster Session

    1. Front Matter
      Pages 1-1
      PDF
    2. CNN-PS: CNN-Based Photometric Stereo for General Non-convex Surfaces
      Satoshi Ikehata
      Pages 3-19
    3. Dynamic Conditional Networks for Few-Shot Learning
      Fang Zhao, Jian Zhao, Shuicheng Yan, Jiashi Feng
      Pages 20-36
    4. Deep Factorised Inverse-Sketching
      Kaiyue Pang, Da Li, Jifei Song, Yi-Zhe Song, Tao Xiang, Timothy M. Hospedales
      Pages 37-54
    5. Look Deeper into Depth: Monocular Depth Estimation with Semantic Booster and Attention-Driven Loss
      Jianbo Jiao, Ying Cao, Yibing Song, Rynson Lau
      Pages 55-71
    6. Summarizing First-Person Videos from Third Persons’ Points of Views
      Hsuan-I Ho, Wei-Chen Chiu, Yu-Chiang Frank Wang
      Pages 72-89
    7. Learning Single-View 3D Reconstruction with Limited Pose Supervision
      Guandao Yang, Yin Cui, Serge Belongie, Bharath Hariharan
      Pages 90-105
    8. Weakly- and Semi-supervised Panoptic Segmentation
      Qizhu Li, Anurag Arnab, Philip H. S. Torr
      Pages 106-124
    9. Making Deep Heatmaps Robust to Partial Occlusions for 3D Object Pose Estimation
      Markus Oberweger, Mahdi Rad, Vincent Lepetit
      Pages 125-141
    10. Deep Co-Training for Semi-Supervised Image Recognition
      Siyuan Qiao, Wei Shen, Zhishuai Zhang, Bo Wang, Alan Yuille
      Pages 142-159
    11. Visual Coreference Resolution in Visual Dialog Using Neural Module Networks
      Satwik Kottur, José M. F. Moura, Devi Parikh, Dhruv Batra, Marcus Rohrbach
      Pages 160-178
    12. Learning Blind Video Temporal Consistency
      Wei-Sheng Lai, Jia-Bin Huang, Oliver Wang, Eli Shechtman, Ersin Yumer, Ming-Hsuan Yang
      Pages 179-195
    13. Salient Objects in Clutter: Bringing Salient Object Detection to the Foreground
      Deng-Ping Fan, Ming-Ming Cheng, Jiang-Jiang Liu, Shang-Hua Gao, Qibin Hou, Ali Borji
      Pages 196-212
    14. Gray-Box Adversarial Training
      B. S. Vivek, Konda Reddy Mopuri, R. Venkatesh Babu
      Pages 213-228
    15. Visual Question Answering as a Meta Learning Task
      Damien Teney, Anton van den Hengel
      Pages 229-245
    16. On Offline Evaluation of Vision-Based Driving Models
      Felipe Codevilla, Antonio M. López, Vladlen Koltun, Alexey Dosovitskiy
      Pages 246-262
    17. Visual Psychophysics for Making Face Recognition Algorithms More Explainable
      Brandon RichardWebster, So Yon Kwon, Christopher Clarizio, Samuel E. Anthony, Walter J. Scheirer
      Pages 263-281
    18. Conditional Prior Networks for Optical Flow
      Yanchao Yang, Stefano Soatto
      Pages 282-298
    19. Robust Optical Flow in Rainy Scenes
      Ruoteng Li, Robby T. Tan, Loong-Fah Cheong
      Pages 299-317
    20. Rethinking Spatiotemporal Feature Learning: Speed-Accuracy Trade-offs in Video Classification
      Saining Xie, Chen Sun, Jonathan Huang, Zhuowen Tu, Kevin Murphy
      Pages 318-335
    21. Variational Wasserstein Clustering
      Liang Mi, Wen Zhang, Xianfeng Gu, Yalin Wang
      Pages 336-352
    22. Show, Tell and Discriminate: Image Captioning by Self-retrieval with Partially Labeled Data
      Xihui Liu, Hongsheng Li, Jing Shao, Dapeng Chen, Xiaogang Wang
      Pages 353-369
    23. Contour Knowledge Transfer for Salient Object Detection
      Xin Li, Fan Yang, Hong Cheng, Wei Liu, Dinggang Shen
      Pages 370-385
    24. Learning Category-Specific Mesh Reconstruction from Image Collections
      Angjoo Kanazawa, Shubham Tulsiani, Alexei A. Efros, Jitendra Malik
      Pages 386-402
    25. Learning to Forecast and Refine Residual Motion for Image-to-Video Generation
      Long Zhao, Xi Peng, Yu Tian, Mubbasir Kapadia, Dimitris Metaxas
      Pages 403-419
    26. Teaching Machines to Understand Baseball Games: Large-Scale Baseball Video Database for Multiple Video Understanding Tasks
      Minho Shim, Young Hwi Kim, Kyungmin Kim, Seon Joo Kim
      Pages 420-437
    27. SketchyScene: Richly-Annotated Scene Sketches
      Changqing Zou, Qian Yu, Ruofei Du, Haoran Mo, Yi-Zhe Song, Tao Xiang et al.
      Pages 438-454
    28. Learn-to-Score: Efficient 3D Scene Exploration by Predicting View Utility
      Benjamin Hepp, Debadeepta Dey, Sudipta N. Sinha, Ashish Kapoor, Neel Joshi, Otmar Hilliges
      Pages 455-472
    29. Revisiting RCNN: On Awakening the Classification Power of Faster RCNN
      Bowen Cheng, Yunchao Wei, Honghui Shi, Rogerio Feris, Jinjun Xiong, Thomas Huang
      Pages 473-490
    30. Semi-supervised Generative Adversarial Hashing for Image Retrieval
      Guan’an Wang, Qinghao Hu, Jian Cheng, Zengguang Hou
      Pages 491-507
    31. Person Re-identification with Deep Similarity-Guided Graph Neural Network
      Yantao Shen, Hongsheng Li, Shuai Yi, Dapeng Chen, Xiaogang Wang
      Pages 508-526
    32. Learning and Matching Multi-View Descriptors for Registration of Point Clouds
      Lei Zhou, Siyu Zhu, Zixin Luo, Tianwei Shen, Runze Zhang, Mingmin Zhen et al.
      Pages 527-544
    33. Revisiting Autofocus for Smartphone Cameras
      Abdullah Abuolaim, Abhijith Punnappurath, Michael S. Brown
      Pages 545-559
    34. Deep Burst Denoising
      Clément Godard, Kevin Matzen, Matt Uyttendaele
      Pages 560-577
    35. ISNN: Impact Sound Neural Network for Audio-Visual Object Classification
      Auston Sterling, Justin Wilson, Sam Lowe, Ming C. Lin
      Pages 578-595
    36. StereoNet: Guided Hierarchical Refinement for Real-Time Edge-Aware Depth Prediction
      Sameh Khamis, Sean Fanello, Christoph Rhemann, Adarsh Kowdle, Julien Valentin, Shahram Izadi
      Pages 596-613
    37. Attention-Aware Deep Adversarial Hashing for Cross-Modal Retrieval
      Xi Zhang, Hanjiang Lai, Jiashi Feng
      Pages 614-629
    38. 3DFeat-Net: Weakly Supervised Local 3D Features for Point Cloud Registration
      Zi Jian Yew, Gim Hee Lee
      Pages 630-646
    39. Deep Domain Generalization via Conditional Invariant Adversarial Networks
      Ya Li, Xinmei Tian, Mingming Gong, Yajing Liu, Tongliang Liu, Kun Zhang et al.
      Pages 647-663
    40. Using LIP to Gloss Over Faces in Single-Stage Face Detection Networks
      Siqi Yang, Arnold Wiliem, Shaokang Chen, Brian C. Lovell
      Pages 664-681
    41. HiDDeN: Hiding Data With Deep Networks
      Jiren Zhu, Russell Kaplan, Justin Johnson, Li Fei-Fei
      Pages 682-697
    42. Multimodal Dual Attention Memory for Video Story Question Answering
      Kyung-Min Kim, Seong-Ho Choi, Jin-Hwa Kim, Byoung-Tak Zhang
      Pages 698-713
    43. Deep Variational Metric Learning
      Xudong Lin, Yueqi Duan, Qiyuan Dong, Jiwen Lu, Jie Zhou
      Pages 714-729
    44. HGMR: Hierarchical Gaussian Mixtures for Adaptive 3D Registration
      Benjamin Eckart, Kihwan Kim, Jan Kautz
      Pages 730-746
    45. Bi-Real Net: Enhancing the Performance of 1-Bit CNNs with Improved Representational Capability and Advanced Training Algorithm
      Zechun Liu, Baoyuan Wu, Wenhan Luo, Xin Yang, Wei Liu, Kwang-Ting Cheng
      Pages 747-763
    46. Orthogonal Deep Features Decomposition for Age-Invariant Face Recognition
      Yitong Wang, Dihong Gong, Zheng Zhou, Xing Ji, Hao Wang, Zhifeng Li et al.
      Pages 764-779
    47. Broadcasting Convolutional Network for Visual Relational Reasoning
      Simyung Chang, John Yang, SeongUk Park, Nojun Kwak
      Pages 780-796
    48. Improving Spatiotemporal Self-supervision by Deep Reinforcement Learning
      Uta Büchler, Biagio Brattoli, Björn Ommer
      Pages 797-814
    49. Learning to Look around Objects for Top-View Representations of Outdoor Scenes
      Samuel Schulter, Menghua Zhai, Nathan Jacobs, Manmohan Chandraker
      Pages 815-831

Other volumes

  1. Computer Vision – ECCV 2018
    15th European Conference, Munich, Germany, September 8-14, 2018, Proceedings, Part I
  2. Computer Vision – ECCV 2018
    15th European Conference, Munich, Germany, September 8-14, 2018, Proceedings, Part II
  3. Computer Vision – ECCV 2018
    15th European Conference, Munich, Germany, September 8–14, 2018, Proceedings, Part III
  4. Computer Vision – ECCV 2018
    15th European Conference, Munich, Germany, September 8-14, 2018, Proceedings, Part IV
  5. Computer Vision – ECCV 2018
    15th European Conference, Munich, Germany, September 8–14, 2018, Proceedings, Part V
  6. Computer Vision – ECCV 2018
    15th European Conference, Munich, Germany, September 8–14, 2018, Proceedings, Part VI
  7. Computer Vision – ECCV 2018
    15th European Conference, Munich, Germany, September 8–14, 2018, Proceedings, Part VII
  8. Computer Vision – ECCV 2018
    15th European Conference, Munich, Germany, September 8-14, 2018, Proceedings, Part VIII
  9. Computer Vision – ECCV 2018
    15th European Conference, Munich, Germany, September 8–14, 2018, Proceedings, Part IX
  10. Computer Vision – ECCV 2018
    15th European Conference, Munich, Germany, September 8-14, 2018, Proceedings, Part X
  11. Computer Vision – ECCV 2018
    15th European Conference, Munich, Germany, September 8-14, 2018, Proceedings, Part XI
  12. Computer Vision – ECCV 2018
    15th European Conference, Munich, Germany, September 8–14, 2018, Proceedings, Part XII
  13. Computer Vision – ECCV 2018
    15th European Conference, Munich, Germany, September 8-14, 2018, Proceedings, Part XIII
  14. Computer Vision – ECCV 2018
    15th European Conference, Munich, Germany, September 8-14, 2018, Proceedings, Part XV
  15. Computer Vision – ECCV 2018
    15th European Conference, Munich, Germany, September 8-14, 2018, Proceedings, Part XVI

About these proceedings

Introduction

The sixteen-volume set comprising the LNCS volumes 11205-11220 constitutes the refereed proceedings of the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018.
The 776 revised papers presented were carefully reviewed and selected from 2439 submissions. The papers are organized in topical sections on learning for vision; computational photography; human analysis; human sensing; stereo and reconstruction; optimization; matching and recognition; video attention; and poster sessions.

Keywords

computer vision machine learning deep neural networks reinforcement learning object recognition image classification image processing object detection semantic segmentation human pose estimation 3d reconstruction stereo vision computational photography

Editors and affiliations

  • Vittorio Ferrari
    • 1
  • Martial Hebert
    • 2
  • Cristian Sminchisescu
    • 3
  • Yair Weiss
    • 4
  1. 1.Google ResearchZurichSwitzerland
  2. 2.Carnegie Mellon UniversityPittsburghUSA
  3. 3.Google ResearchZurichSwitzerland
  4. 4.Hebrew University of JerusalemJerusalemIsrael

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-030-01267-0
  • Copyright Information Springer Nature Switzerland AG 2018
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-030-01266-3
  • Online ISBN 978-3-030-01267-0
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site