Deep video representation learning: a survey

Published: 01 Jan 2024, Last Modified: 05 Mar 2025Multim. Tools Appl. 2024EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: This paper provides a review on representation learning for videos. We classify recent spatio-temporal feature learning methods for sequential visual data and compare their pros and cons for general video analysis. Building effective features for videos is a fundamental problem in computer vision tasks involving video analysis and understanding. Existing features can be generally categorized into spatial and temporal features. Their effectiveness under variations of illumination, occlusion, view and background are discussed. Finally, we discuss the remaining challenges in existing deep video representation learning studies.
Loading