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Computer Vision – ECCV 2016

Overview of attention for book
Computer Vision – ECCV 2016
Springer, Cham

Table of Contents

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    Book Overview
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    Chapter 1 Generating Visual Explanations
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    Chapter 2 Marker-Less 3D Human Motion Capture with Monocular Image Sequence and Height-Maps
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    Chapter 3 Tensor Representations via Kernel Linearization for Action Recognition from 3D Skeletons
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    Chapter 4 Manhattan-World Urban Reconstruction from Point Clouds
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    Chapter 5 Computer Vision – ECCV 2016
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    Chapter 6 Shape from Selfies: Human Body Shape Estimation Using CCA Regression Forests
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    Chapter 7 Can We Jointly Register and Reconstruct Creased Surfaces by Shape-from-Template Accurately?
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    Chapter 8 Distractor-Supported Single Target Tracking in Extremely Cluttered Scenes
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    Chapter 9 Connectionist Temporal Modeling for Weakly Supervised Action Labeling
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    Chapter 10 Deep Joint Image Filtering
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    Chapter 11 Efficient Multi-frequency Phase Unwrapping Using Kernel Density Estimation
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    Chapter 12 A Multi-scale CNN for Affordance Segmentation in RGB Images
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    Chapter 13 Hierarchical Dynamic Parsing and Encoding for Action Recognition
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    Chapter 14 Distinct Class-Specific Saliency Maps for Weakly Supervised Semantic Segmentation
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    Chapter 15 A Diagram is Worth a Dozen Images
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    Chapter 16 Automatic Attribute Discovery with Neural Activations
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    Chapter 17 “What Happens If...” Learning to Predict the Effect of Forces in Images
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    Chapter 18 View Synthesis by Appearance Flow
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    Chapter 19 Top-Down Learning for Structured Labeling with Convolutional Pseudoprior
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    Chapter 20 Generative Image Modeling Using Style and Structure Adversarial Networks
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    Chapter 21 Joint Learning of Semantic and Latent Attributes
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    Chapter 22 A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection
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    Chapter 23 Deep Specialized Network for Illuminant Estimation
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    Chapter 24 Weakly-Supervised Semantic Segmentation Using Motion Cues
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    Chapter 25 Human-in-the-Loop Person Re-identification
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    Chapter 26 Real-Time Monocular Segmentation and Pose Tracking of Multiple Objects
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    Chapter 27 Estimation of Human Body Shape in Motion with Wide Clothing
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    Chapter 28 A Shape-Based Approach for Salient Object Detection Using Deep Learning
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    Chapter 29 Fast Optical Flow Using Dense Inverse Search
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    Chapter 30 Global Registration of 3D Point Sets via LRS Decomposition
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    Chapter 31 Recognition from Hand Cameras: A Revisit with Deep Learning
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    Chapter 32 XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks
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    Chapter 33 Top-Down Neural Attention by Excitation Backprop
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    Chapter 34 Learning Recursive Filters for Low-Level Vision via a Hybrid Neural Network
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    Chapter 35 Learning Representations for Automatic Colorization
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    Chapter 36 Deep Reconstruction-Classification Networks for Unsupervised Domain Adaptation
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    Chapter 37 Learning Without Forgetting
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    Chapter 38 Identity Mappings in Deep Residual Networks
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    Chapter 39 Deep Networks with Stochastic Depth
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    Chapter 40 Less Is More: Towards Compact CNNs
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    Chapter 41 Unsupervised Visual Representation Learning by Graph-Based Consistent Constraints
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    Chapter 42 Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation
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    Chapter 43 Patch-Based Low-Rank Matrix Completion for Learning of Shape and Motion Models from Few Training Samples
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    Chapter 44 Chained Predictions Using Convolutional Neural Networks
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    Chapter 45 Multi-region Two-Stream R-CNN for Action Detection
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    Chapter 46 Semantic Co-segmentation in Videos
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    Chapter 47 Attribute2Image: Conditional Image Generation from Visual Attributes
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    Chapter 48 Modeling Context Between Objects for Referring Expression Understanding
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    Chapter 49 Friction from Reflectance: Deep Reflectance Codes for Predicting Physical Surface Properties from One-Shot In-Field Reflectance
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    Chapter 50 Saliency Detection with Recurrent Fully Convolutional Networks
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    Chapter 51 Deep3D: Fully Automatic 2D-to-3D Video Conversion with Deep Convolutional Neural Networks
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    Chapter 52 Temporal Model Adaptation for Person Re-identification
Attention for Chapter 32: XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks
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Chapter title
XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks
Chapter number 32
Book title
Computer Vision – ECCV 2016
Published by
Springer, Cham, October 2016
DOI 10.1007/978-3-319-46493-0_32
Book ISBNs
978-3-31-946492-3, 978-3-31-946493-0
Authors

Mohammad Rastegari, Vicente Ordonez, Joseph Redmon, Ali Farhadi, Rastegari, Mohammad, Ordonez, Vicente, Redmon, Joseph, Farhadi, Ali

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2,293 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 <1%
Germany 3 <1%
Japan 3 <1%
Ireland 2 <1%
Spain 2 <1%
Russia 2 <1%
Italy 2 <1%
Israel 2 <1%
Australia 2 <1%
Other 13 <1%
Unknown 2253 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 523 23%
Student > Master 459 20%
Researcher 262 11%
Student > Bachelor 209 9%
Other 106 5%
Other 230 10%
Unknown 504 22%
Readers by discipline Count As %
Computer Science 1075 47%
Engineering 497 22%
Mathematics 34 1%
Physics and Astronomy 33 1%
Neuroscience 18 <1%
Other 76 3%
Unknown 560 24%

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