VUDG is a domain-generalization benchmark for video understanding with 11 domains and 36,388 QA pairs, and it shows that current large video-language models lose accuracy across visual domains.
Mar: Masked autoencoders for efficient action recognition.IEEE Transactions on Multimedia, 26:218–233, 2023
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
VUDG: A Dataset for Video Understanding Domain Generalization
VUDG is a domain-generalization benchmark for video understanding with 11 domains and 36,388 QA pairs, and it shows that current large video-language models lose accuracy across visual domains.