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Computer Vision – ECCV 2018

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Table of Contents

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    Book Overview
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    Chapter 1 Snap Angle Prediction for 360 $$^{\circ }$$ ∘ Panoramas
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    Chapter 2 Unsupervised Holistic Image Generation from Key Local Patches
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    Chapter 3 DF-Net: Unsupervised Joint Learning of Depth and Flow Using Cross-Task Consistency
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    Chapter 4 Neural Stereoscopic Image Style Transfer
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    Chapter 5 Transductive Centroid Projection for Semi-supervised Large-Scale Recognition
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    Chapter 6 Generalized Loss-Sensitive Adversarial Learning with Manifold Margins
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    Chapter 7 Into the Twilight Zone: Depth Estimation Using Joint Structure-Stereo Optimization
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    Chapter 8 Recycle-GAN: Unsupervised Video Retargeting
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    Chapter 9 Fine-Grained Video Categorization with Redundancy Reduction Attention
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    Chapter 10 Open Set Domain Adaptation by Backpropagation
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    Chapter 11 Deep Feature Pyramid Reconfiguration for Object Detection
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    Chapter 12 Goal-Oriented Visual Question Generation via Intermediate Rewards
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    Chapter 13 DeepGUM: Learning Deep Robust Regression with a Gaussian-Uniform Mixture Model
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    Chapter 14 Estimating the Success of Unsupervised Image to Image Translation
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    Chapter 15 Parallel Feature Pyramid Network for Object Detection
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    Chapter 16 Joint Map and Symmetry Synchronization
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    Chapter 17 MT-VAE: Learning Motion Transformations to Generate Multimodal Human Dynamics
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    Chapter 18 Rethinking the Form of Latent States in Image Captioning
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    Chapter 19 Transductive Semi-Supervised Deep Learning Using Min-Max Features
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    Chapter 20 SAN: Learning Relationship Between Convolutional Features for Multi-scale Object Detection
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    Chapter 21 Hashing with Binary Matrix Pursuit
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    Chapter 22 MaskConnect: Connectivity Learning by Gradient Descent
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    Chapter 23 Online Multi-Object Tracking with Dual Matching Attention Networks
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    Chapter 24 Connecting Gaze, Scene, and Attention: Generalized Attention Estimation via Joint Modeling of Gaze and Scene Saliency
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    Chapter 25 Videos as Space-Time Region Graphs
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    Chapter 26 Unified Perceptual Parsing for Scene Understanding
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    Chapter 27 Synthetically Supervised Feature Learning for Scene Text Recognition
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    Chapter 28 Probabilistic Video Generation Using Holistic Attribute Control
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    Chapter 29 Learning Rigidity in Dynamic Scenes with a Moving Camera for 3D Motion Field Estimation
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    Chapter 30 Unsupervised CNN-Based Co-saliency Detection with Graphical Optimization
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    Chapter 31 Mutual Learning to Adapt for Joint Human Parsing and Pose Estimation
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    Chapter 32 DCAN: Dual Channel-Wise Alignment Networks for Unsupervised Scene Adaptation
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    Chapter 33 View-Graph Selection Framework for SfM
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    Chapter 34 Selfie Video Stabilization
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    Chapter 35 CubeNet: Equivariance to 3D Rotation and Translation
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    Chapter 36 YouTube-VOS: Sequence-to-Sequence Video Object Segmentation
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    Chapter 37 PPF-FoldNet: Unsupervised Learning of Rotation Invariant 3D Local Descriptors
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    Chapter 38 In the Eye of Beholder: Joint Learning of Gaze and Actions in First Person Video
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    Chapter 39 Double JPEG Detection in Mixed JPEG Quality Factors Using Deep Convolutional Neural Network
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    Chapter 40 Wasserstein Divergence for GANs
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    Chapter 41 Semi-supervised FusedGAN for Conditional Image Generation
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    Chapter 42 Pose Partition Networks for Multi-person Pose Estimation
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    Chapter 43 Understanding Degeneracies and Ambiguities in Attribute Transfer
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    Chapter 44 Reinforced Temporal Attention and Split-Rate Transfer for Depth-Based Person Re-identification
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    Chapter 45 Scale Aggregation Network for Accurate and Efficient Crowd Counting
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    Chapter 46 Deep Shape Matching
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    Chapter 47 Eigendecomposition-Free Training of Deep Networks with Zero Eigenvalue-Based Losses
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    Chapter 48 Visual Reasoning with Multi-hop Feature Modulation
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Title
Computer Vision – ECCV 2018
Published by
Springer International Publishing, December 2018
DOI 10.1007/978-3-030-01228-1
ISBNs
978-3-03-001227-4, 978-3-03-001228-1
Editors

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

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X Demographics

The data shown below were collected from the profiles of 8 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 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 30%
Student > Master 5 22%
Student > Bachelor 2 9%
Researcher 1 4%
Professor > Associate Professor 1 4%
Other 0 0%
Unknown 7 30%
Readers by discipline Count As %
Computer Science 13 57%
Arts and Humanities 1 4%
Medicine and Dentistry 1 4%
Engineering 1 4%
Unknown 7 30%