Temporal models for video

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Table of contents

1 Introduction 
1.1 Goal
1.2 Motivation
1.3 Challenges
1.4 Contributions and outline
2 Related Work 
2.1 Images and text
2.1.1 Image captioning
2.1.2 Text as supervision
2.2 Video and text
2.2.1 Weak supervision
2.2.2 Datasets
2.2.3 Captioning
2.2.4 Alignment
2.3 Temporal models for video
2.3.1 Action models
2.3.2 Composite activities
2.4 Learning and optimization
2.4.1 Discriminative clustering
2.4.2 Frank-Wolfe
3 Background 
3.1 Learning and supervision
3.1.1 Fully-supervised learning
3.1.2 Weakly-supervised learning
3.1.3 Unsupervised learning
3.1.4 Semi-supervised learning
3.2 Clustering
3.2.1 Generative clustering
3.2.2 Discriminative clustering
3.2.3 DIFFRAC
3.2.4 Adding constraints
4 Weakly supervised labeling of persons and actions in movies 
4.1 Introduction
4.1.1 Contributions of this chapter
4.2 Joint Model of characters and Actions
4.2.1 Notations and problem formulation
4.2.2 Discriminative loss
4.2.3 Grouping term
4.2.4 Constraints on latent variables
4.2.5 Slack Variables
4.3 Optimization
4.3.1 Relaxation
4.3.2 Splitting the Optimization
4.3.3 Rounding
4.4 Relation to Diffrac [Bach and Harchaoui, 2007]
4.5 Features and Dataset
4.5.1 Text processing
4.5.2 Video features
4.5.3 Dataset
4.6 Experiments
4.6.1 Learning names : controlled set-up
4.6.2 Comparison with other weakly supervised methods
4.6.3 Learning names and actions
4.6.4 Improvements
4.7 Conclusion and future work
5 A convex relaxation and efficient algorithm for aligning video and text 
5.1 Introduction
5.2 Proposed model
5.2.1 Problem statement and approach
5.2.2 Basic model
5.2.3 Priors and constraints
5.2.4 Full problem formulation
5.3 Optimization
5.3.1 Relaxation
5.3.2 The Frank-Wolfe Algorithm
5.3.3 Minimizing Linear Functions over 𝒵 by dynamic programming
5.3.4 Rounding
5.4 Semi-supervised setting
5.5 Experimental evaluation
5.5.1 Controlled setup
5.5.2 Aligning sequences of actions [Bojanowski et al., 2014]
5.5.3 Text-to-video alignment
5.6 Conclusion and discussion
6 Conclusion 
A Zero eigenvalues of 𝑄