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Foundation Models for Video Understanding: A Survey
May 8, 2024, 4:45 a.m. | Neelu Madan, Andreas Moegelmose, Rajat Modi, Yogesh S. Rawat, Thomas B. Moeslund
cs.CV updates on arXiv.org arxiv.org
Abstract: Video Foundation Models (ViFMs) aim to learn a general-purpose representation for various video understanding tasks. Leveraging large-scale datasets and powerful models, ViFMs achieve this by capturing robust and generic features from video data. This survey analyzes over 200 video foundational models, offering a comprehensive overview of benchmarks and evaluation metrics across 14 distinct video tasks categorized into 3 main categories. Additionally, we offer an in-depth performance analysis of these models for the 6 most common …
arxiv cs.cv foundation survey type understanding video video understanding
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