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Computer Vision – ECCV 2018 Workshops

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Cover of 'Computer Vision – ECCV 2018 Workshops'

Table of Contents

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    Book Overview
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    Chapter 1 Fast Semantic Segmentation on Video Using Block Motion-Based Feature Interpolation
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    Chapter 2 Video Object Segmentation with Referring Expressions
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    Chapter 3 MobileFace: 3D Face Reconstruction with Efficient CNN Regression
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    Chapter 4 A Kinematic Chain Space for Monocular Motion Capture
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    Chapter 5 Non-rigid 3D Shape Registration Using an Adaptive Template
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    Chapter 6 3D Human Body Reconstruction from a Single Image via Volumetric Regression
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    Chapter 7 Can 3D Pose Be Learned from 2D Projections Alone?
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    Chapter 8 Towards a Fair Evaluation of Zero-Shot Action Recognition Using External Data
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    Chapter 9 MoQA – A Multi-modal Question Answering Architecture
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    Chapter 10 Pre-gen Metrics: Predicting Caption Quality Metrics Without Generating Captions
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    Chapter 11 Pre-gen metrics: Predicting caption quality metrics without generating captions
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    Chapter 11 Quantifying the Amount of Visual Information Used by Neural Caption Generators
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    Chapter 12 Distinctive-Attribute Extraction for Image Captioning
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    Chapter 13 Knowing Where to Look? Analysis on Attention of Visual Question Answering System
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    Chapter 14 Knowing When to Look for What and Where: Evaluating Generation of Spatial Descriptions with Adaptive Attention
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    Chapter 15 How Clever Is the FiLM Model, and How Clever Can it Be?
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    Chapter 16 Image-Sensitive Language Modeling for Automatic Speech Recognition
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    Chapter 17 Adding Object Detection Skills to Visual Dialogue Agents
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    Chapter 18 The 2nd YouTube-8M Large-Scale Video Understanding Challenge
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    Chapter 19 NeXtVLAD: An Efficient Neural Network to Aggregate Frame-Level Features for Large-Scale Video Classification
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    Chapter 20 Non-local NetVLAD Encoding for Video Classification
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    Chapter 21 Learnable Pooling Methods for Video Classification
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    Chapter 22 Constrained-Size Tensorflow Models for YouTube-8M Video Understanding Challenge
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    Chapter 23 Label Denoising with Large Ensembles of Heterogeneous Neural Networks
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    Chapter 24 Hierarchical Video Frame Sequence Representation with Deep Convolutional Graph Network
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    Chapter 25 Training Compact Deep Learning Models for Video Classification Using Circulant Matrices
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    Chapter 26 Towards Good Practices for Multi-modal Fusion in Large-Scale Video Classification
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    Chapter 27 Building A Size Constrained Predictive Models for Video Classification
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    Chapter 28 Temporal Attention Mechanism with Conditional Inference for Large-Scale Multi-label Video Classification
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    Chapter 29 Approach for Video Classification with Multi-label on YouTube-8M Dataset
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    Chapter 30 Learning Video Features for Multi-label Classification
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    Chapter 31 Large-Scale Video Classification with Feature Space Augmentation Coupled with Learned Label Relations and Ensembling
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    Chapter 32 Multi-style Generative Network for Real-Time Transfer
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    Chapter 33 Frustratingly Easy Trade-off Optimization Between Single-Stage and Two-Stage Deep Object Detectors
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    Chapter 34 Targeted Kernel Networks: Faster Convolutions with Attentive Regularization
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    Chapter 35 Small Defect Detection Using Convolutional Neural Network Features and Random Forests
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    Chapter 36 Compact Deep Aggregation for Set Retrieval
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    Chapter 37 Adversarial Network Compression
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    Chapter 38 Target Aware Network Adaptation for Efficient Representation Learning
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    Chapter 39 Learning CCA Representations for Misaligned Data
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    Chapter 40 Learning Relationship-Aware Visual Features
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    Chapter 41 DNN Feature Map Compression Using Learned Representation over GF(2)
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    Chapter 42 LBP-Motivated Colour Texture Classification
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    Chapter 43 Discriminative Feature Selection by Optimal Manifold Search for Neoplastic Image Recognition
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    Chapter 44 Fast, Visual and Interactive Semi-supervised Dimensionality Reduction
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    Chapter 45 Efficient Texture Retrieval Using Multiscale Local Extrema Descriptors and Covariance Embedding
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    Chapter 46 Extended Non-local Feature for Visual Saliency Detection in Low Contrast Images
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    Chapter 47 Incomplete Multi-view Clustering via Graph Regularized Matrix Factorization
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    Chapter 48 GA-Based Filter Selection for Representation in Convolutional Neural Networks
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    Chapter 49 Active Descriptor Learning for Feature Matching
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    Chapter 50 A Joint Generative Model for Zero-Shot Learning
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    Chapter 51 WiCV at ECCV2018: The Fifth Women in Computer Vision Workshop
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    Chapter 52 Gait Energy Image Reconstruction from Degraded Gait Cycle Using Deep Learning
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    Chapter 53 Hierarchical Video Understanding
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    Chapter 54 Fine-Grained Vehicle Classification with Unsupervised Parts Co-occurrence Learning
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    Chapter 55 Multiple Wavelet Pooling for CNNs
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    Chapter 56 Automated Facial Wrinkles Annotator
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    Chapter 57 Deep Learning of Appearance Models for Online Object Tracking
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    Chapter 58 Towards Cycle-Consistent Models for Text and Image Retrieval
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    Chapter 59 From Attribute-Labels to Faces: Face Generation Using a Conditional Generative Adversarial Network
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    Chapter 60 Optimizing Body Region Classification with Deep Convolutional Activation Features
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    Chapter 61 Efficient Interactive Multi-object Segmentation in Medical Images
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    Chapter 62 Cross-modal Embeddings for Video and Audio Retrieval
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    Chapter 63 Understanding Center Loss Based Network for Image Retrieval with Few Training Data
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    Chapter 64 End-to-End Trained CNN Encoder-Decoder Networks for Image Steganography
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    Chapter 65 Cancelable Knuckle Template Generation Based on LBP-CNN
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    Chapter 66 A 2.5D Deep Learning-Based Approach for Prostate Cancer Detection on T2-Weighted Magnetic Resonance Imaging
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    Chapter 67 GreenWarps: A Two-Stage Warping Model for Stitching Images Using Diffeomorphic Meshes and Green Coordinates
Overall attention for this book and its chapters
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Mentioned by

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6 X users
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1 Wikipedia page

Citations

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Title
Computer Vision – ECCV 2018 Workshops
Published by
Springer International Publishing, March 2019
DOI 10.1007/978-3-030-11018-5
ISBNs
978-3-03-011017-8, 978-3-03-011018-5
Editors

Leal-Taixé, Laura, Roth, Stefan

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X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 38%
Student > Master 2 13%
Researcher 1 6%
Unknown 7 44%
Readers by discipline Count As %
Computer Science 5 31%
Engineering 3 19%
Unknown 8 50%

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