Instruct: Given a paper title, retrieve paper titles that are cited by the given paper.
Query: Finding Actors and Actions in Movies
Learning realistic human actions from movies
Watch-n-Patch: Unsupervised Learning of Actions and Relations
HUMAN ACTION RECOGNITION IN VIDEOS : A SURVEY
Objects2action: Classifying and Localizing Actions without Any Video Example
Action Search: Spotting Actions in Videos and Its Application to Temporal Action Localization
Highlight Detection in Movie Scenes Through Inter-users, Physiological Linkage
Action Search: Learning to Search for Human Activities in Untrimmed Videos
Unsupervised Induction of Contingent Event Pairs from Film Scenes
Automatically selecting shots for action movie trailers
Automatic annotation of human actions in video
Leveraging Long and Short-term Information in Content-aware Movie Recommendation
Neural Events Extraction from Movie Descriptions
Recognizing realistic actions from videos “in the wild”
CoCharNet: Extracting Social Networks using Character Co-occurrence in Movies
Unsupervised alignment of actions in video with text descriptions
A data mining approach to analysis and prediction of movie
Natural Language Description of Human Activities from Video Images Based on Concept Hierarchy of Actions
From Trailers to Storylines: An Efficient Way to Learn from Movies
Exploring the Semantic Gap for Movie Recommendations
CTC Network with Statistical Language Modeling for Action Sequence Recognition in Videos
A Bayesian Framework for Multi-cue 3D Object Tracking
Dolphin Shows and Interaction Programs: Benefits for Conservation Education?
Concurrent filtering and smoothing: A parallel architecture for real-time navigation and full smoothing
Supervised Learning of Semantic Classes for Image Annotation and Retrieval
Transient fault detection via simultaneous multithreading