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Computer Vision – ECCV 2020

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Table of Contents

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    Book Overview
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    Chapter 1 Partially-Shared Variational Auto-encoders for Unsupervised Domain Adaptation with Target Shift
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    Chapter 2 Learning Where to Focus for Efficient Video Object Detection
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    Chapter 3 Learning Object Permanence from Video
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    Chapter 4 Adaptive Text Recognition Through Visual Matching
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    Chapter 5 Actions as Moving Points
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    Chapter 6 Learning to Exploit Multiple Vision Modalities by Using Grafted Networks
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    Chapter 7 Geometric Correspondence Fields: Learned Differentiable Rendering for 3D Pose Refinement in the Wild
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    Chapter 8 3D Fluid Flow Reconstruction Using Compact Light Field PIV
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    Chapter 9 Contextual Diversity for Active Learning
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    Chapter 10 Temporal Aggregate Representations for Long-Range Video Understanding
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    Chapter 11 Stochastic Fine-Grained Labeling of Multi-state Sign Glosses for Continuous Sign Language Recognition
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    Chapter 12 General 3D Room Layout from a Single View by Render-and-Compare
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    Chapter 13 Neural Dense Non-Rigid Structure from Motion with Latent Space Constraints
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    Chapter 14 Multimodal Memorability: Modeling Effects of Semantics and Decay on Video Memorability
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    Chapter 15 Yet Another Intermediate-Level Attack
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    Chapter 16 Topology-Change-Aware Volumetric Fusion for Dynamic Scene Reconstruction
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    Chapter 17 Early Exit or Not: Resource-Efficient Blind Quality Enhancement for Compressed Images
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    Chapter 18 PatchNets: Patch-Based Generalizable Deep Implicit 3D Shape Representations
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    Chapter 19 How Does Lipschitz Regularization Influence GAN Training?
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    Chapter 20 Infrastructure-Based Multi-camera Calibration Using Radial Projections
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    Chapter 21 MotionSqueeze: Neural Motion Feature Learning for Video Understanding
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    Chapter 22 Polarized Optical-Flow Gyroscope
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    Chapter 23 Online Meta-learning for Multi-source and Semi-supervised Domain Adaptation
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    Chapter 24 An Ensemble of Epoch-Wise Empirical Bayes for Few-Shot Learning
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    Chapter 25 On the Effectiveness of Image Rotation for Open Set Domain Adaptation
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    Chapter 26 Combining Task Predictors via Enhancing Joint Predictability
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    Chapter 27 Multi-scale Positive Sample Refinement for Few-Shot Object Detection
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    Chapter 28 Single-Image Depth Prediction Makes Feature Matching Easier
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    Chapter 29 Deep Reinforced Attention Learning for Quality-Aware Visual Recognition
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    Chapter 30 CFAD: Coarse-to-Fine Action Detector for Spatiotemporal Action Localization
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    Chapter 31 Learning Joint Spatial-Temporal Transformations for Video Inpainting
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    Chapter 32 Single Path One-Shot Neural Architecture Search with Uniform Sampling
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    Chapter 33 Learning to Generate Novel Domains for Domain Generalization
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    Chapter 34 Continuous Adaptation for Interactive Object Segmentation by Learning from Corrections
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    Chapter 35 Impact of Base Dataset Design on Few-Shot Image Classification
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    Chapter 36 Invertible Zero-Shot Recognition Flows
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    Chapter 37 GeoLayout: Geometry Driven Room Layout Estimation Based on Depth Maps of Planes
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    Chapter 38 Location Sensitive Image Retrieval and Tagging
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    Chapter 39 Joint 3D Layout and Depth Prediction from a Single Indoor Panorama Image
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    Chapter 40 Guessing State Tracking for Visual Dialogue
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    Chapter 41 Memory-Efficient Incremental Learning Through Feature Adaptation
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    Chapter 42 Neural Voice Puppetry: Audio-Driven Facial Reenactment
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    Chapter 43 One-Shot Unsupervised Cross-Domain Detection
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    Chapter 44 Stochastic Frequency Masking to Improve Super-Resolution and Denoising Networks
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    Chapter 45 Probabilistic Future Prediction for Video Scene Understanding
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    Chapter 46 Suppressing Mislabeled Data via Grouping and Self-attention
Attention for Chapter 21: MotionSqueeze: Neural Motion Feature Learning for Video Understanding
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Chapter title
MotionSqueeze: Neural Motion Feature Learning for Video Understanding
Chapter number 21
Book title
Computer Vision – ECCV 2020
Published by
Springer, Cham, August 2020
DOI 10.1007/978-3-030-58517-4_21
Book ISBNs
978-3-03-058516-7, 978-3-03-058517-4
Authors

Heeseung Kwon, Manjin Kim, Suha Kwak, Minsu Cho, Kwon, Heeseung, Kim, Manjin, Kwak, Suha, Cho, Minsu

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 168 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 168 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 29 17%
Student > Ph. D. Student 23 14%
Researcher 14 8%
Student > Bachelor 9 5%
Student > Doctoral Student 6 4%
Other 11 7%
Unknown 76 45%
Readers by discipline Count As %
Computer Science 70 42%
Engineering 12 7%
Social Sciences 2 1%
Mathematics 1 <1%
Agricultural and Biological Sciences 1 <1%
Other 3 2%
Unknown 79 47%