OpenVMR uses normalizing flow to detect out-of-distribution queries and performs moment retrieval only on in-distribution queries.
Computing Research Repository arXiv Preprint, arXiv:2001.09308 (2020)
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Models frames and words as cooperative game players to value uncertain vision-language correspondences for proposal-free moment localization, reporting superior results on Charades-STA and ActivityNet Caption.
MCMT improves weakly-supervised VMR by fusing multiple learnable Gaussian masks from proposals into a positive sample mask and using dual masked query reconstruction tasks for stability.
citing papers explorer
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Not All Inputs Are Valid: Towards Open-Set Video Moment Retrieval Using Language
OpenVMR uses normalizing flow to detect out-of-distribution queries and performs moment retrieval only on in-distribution queries.
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Rethinking Weakly-supervised Video Temporal Grounding From a Game Perspective
Models frames and words as cooperative game players to value uncertain vision-language correspondences for proposal-free moment localization, reporting superior results on Charades-STA and ActivityNet Caption.
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Multi-proposal Collaboration and Multi-task Training for Weakly-supervised Video Moment Retrieval
MCMT improves weakly-supervised VMR by fusing multiple learnable Gaussian masks from proposals into a positive sample mask and using dual masked query reconstruction tasks for stability.