The paper proposes a text-motion contrastive loss (TMCCL) that improves video memorability prediction and a memorability-weighted correction for video summarization, but the loss as written has a sign error.
Quo vadis, action recognition? a new model and the kinetics dataset, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
other 1
citation-polarity summary
fields
cs.CV 1years
2025 1verdicts
REJECT 1roles
other 1polarities
unclear 1representative citing papers
citing papers explorer
-
Enhancing Video Memorability Prediction with Text-Motion Cross-modal Contrastive Loss and Its Application in Video Summarization
The paper proposes a text-motion contrastive loss (TMCCL) that improves video memorability prediction and a memorability-weighted correction for video summarization, but the loss as written has a sign error.