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Computer Vision – ECCV 2018

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Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Shift-Net: Image Inpainting via Deep Feature Rearrangement
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    Chapter 2 Interactive Boundary Prediction for Object Selection
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    Chapter 3 X-Ray Computed Tomography Through Scatter
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    Chapter 4 Video Re-localization
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    Chapter 5 Mask TextSpotter: An End-to-End Trainable Neural Network for Spotting Text with Arbitrary Shapes
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    Chapter 6 DFT-based Transformation Invariant Pooling Layer for Visual Classification
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    Chapter 7 Appearance-Based Gaze Estimation via Evaluation-Guided Asymmetric Regression
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    Chapter 8 ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design
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    Chapter 9 Deep Clustering for Unsupervised Learning of Visual Features
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    Chapter 10 Modular Generative Adversarial Networks
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    Chapter 11 Graph Distillation for Action Detection with Privileged Modalities
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    Chapter 12 Weakly-Supervised Video Summarization Using Variational Encoder-Decoder and Web Prior
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    Chapter 13 Single Image Intrinsic Decomposition Without a Single Intrinsic Image
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    Chapter 14 Learning to Dodge A Bullet: Concyclic View Morphing via Deep Learning
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    Chapter 15 Compositional Learning for Human Object Interaction
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    Chapter 16 Viewpoint Estimation—Insights and Model
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    Chapter 17 PersonLab: Person Pose Estimation and Instance Segmentation with a Bottom-Up, Part-Based, Geometric Embedding Model
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    Chapter 18 Task-Driven Webpage Saliency
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    Chapter 19 Deep Image Demosaicking Using a Cascade of Convolutional Residual Denoising Networks
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    Chapter 20 A New Large Scale Dynamic Texture Dataset with Application to ConvNet Understanding
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    Chapter 21 Deep Feature Factorization for Concept Discovery
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    Chapter 22 Deep Regression Tracking with Shrinkage Loss
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    Chapter 23 Dist-GAN: An Improved GAN Using Distance Constraints
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    Chapter 24 Pivot Correlational Neural Network for Multimodal Video Categorization
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    Chapter 25 Part-Aligned Bilinear Representations for Person Re-identification
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    Chapter 26 Learning to Navigate for Fine-Grained Classification
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    Chapter 27 NAM: Non-Adversarial Unsupervised Domain Mapping
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    Chapter 28 Transferable Adversarial Perturbations
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    Chapter 29 Semantically Aware Urban 3D Reconstruction with Plane-Based Regularization
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    Chapter 30 Joint 3D Tracking of a Deformable Object in Interaction with a Hand
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    Chapter 31 HBE: Hand Branch Ensemble Network for Real-Time 3D Hand Pose Estimation
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    Chapter 32 Sequential Clique Optimization for Video Object Segmentation
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    Chapter 33 Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network
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    Chapter 34 Efficient Relative Attribute Learning Using Graph Neural Networks
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    Chapter 35 Deep Kalman Filtering Network for Video Compression Artifact Reduction
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    Chapter 36 A Deeply-Initialized Coarse-to-fine Ensemble of Regression Trees for Face Alignment
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    Chapter 37 DeepVS: A Deep Learning Based Video Saliency Prediction Approach
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    Chapter 38 Learning Efficient Single-Stage Pedestrian Detectors by Asymptotic Localization Fitting
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    Chapter 39 Scenes-Objects-Actions: A Multi-task, Multi-label Video Dataset
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    Chapter 40 Accelerating Dynamic Programs via Nested Benders Decomposition with Application to Multi-Person Pose Estimation
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    Chapter 41 Human Motion Analysis with Deep Metric Learning
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    Chapter 42 Exploring Visual Relationship for Image Captioning
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    Chapter 43 Single Shot Scene Text Retrieval
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    Chapter 44 Folded Recurrent Neural Networks for Future Video Prediction
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    Chapter 45 CornerNet: Detecting Objects as Paired Keypoints
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    Chapter 46 RelocNet: Continuous Metric Learning Relocalisation Using Neural Nets
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    Chapter 47 The Contextual Loss for Image Transformation with Non-aligned Data
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    Chapter 48 Acquisition of Localization Confidence for Accurate Object Detection
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    Chapter 49 Deep Model-Based 6D Pose Refinement in RGB
Overall attention for this book and its chapters
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Title
Computer Vision – ECCV 2018
Published by
Springer International Publishing, December 2018
DOI 10.1007/978-3-030-01264-9
ISBNs
978-3-03-001263-2, 978-3-03-001264-9
Editors

Ferrari, Vittorio, Hebert, Martial, Sminchisescu, Cristian, Weiss, Yair

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 59 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 10%
Student > Doctoral Student 5 8%
Student > Postgraduate 5 8%
Student > Master 5 8%
Lecturer 3 5%
Other 7 12%
Unknown 28 47%
Readers by discipline Count As %
Computer Science 23 39%
Engineering 5 8%
Psychology 1 2%
Unknown 30 51%