Partial Annotation-based Video Moment Retrieval via Iterative Learning
Wei Ji, Renjie Liang, Lizi Liao, Hao Fei, Fuli Feng
Abstract
Given a descriptive language query, Video Moment Retrieval (VMR) aims to seek the corresponding semantic-consistent moment clip in the video, which is represented as a pair of the start and end timestamps. Although current methods have achieved satisfying performance, training these models heavily relies on the fully-annotated VMR datasets. Nonetheless, precise video temporal annotations are extremely labor-intensive and ambiguous due to the diverse preferences of different annotators.
Topics & Concepts
Computer scienceTimestampMoment (physics)AnnotationInformation retrievalArtificial intelligenceReal-time computingClassical mechanicsPhysicsVideo Analysis and SummarizationMultimodal Machine Learning ApplicationsHuman Pose and Action Recognition