Partially Relevant Video Retrieval
5 papers with code • 3 benchmarks • 3 datasets
In the Partially Relevant Video Retrieval (PRVR) task, an untrimmed video is considered to be partially relevant w.r.t. a given textual query if it contains a moment relevant to the query. PRVR aims to retrieve such partially relevant videos from a large collection of untrimmed videos.
Benchmarks
These leaderboards are used to track progress in Partially Relevant Video Retrieval
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ActivityNet Captions
Charades-STA
TVR
Most implemented papers
Partially Relevant Video Retrieval
HuiGuanLab/ms-sl
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To fill the gap, we propose in this paper a novel T2VR subtask termed Partially Relevant Video Retrieval (PRVR).
Dual Learning with Dynamic Knowledge Distillation for Partially Relevant Video Retrieval
huiguanlab/dl-dkd
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ICCV 2023
During the knowledge distillation, an inheritance student branch is devised to absorb the knowledge from the teacher model.
GMMFormer: Gaussian-Mixture-Model Based Transformer for Efficient Partially Relevant Video Retrieval
Current PRVR methods adopt scanning-based clip construction to achieve explicit clip modeling, which is information-redundant and requires a large storage overhead.
GMMFormer v2: An Uncertainty-aware Framework for Partially Relevant Video Retrieval
huangmozhi9527/gmmformer_v2
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Given a text query, partially relevant video retrieval (PRVR) aims to retrieve untrimmed videos containing relevant moments.
Towards Efficient Partially Relevant Video Retrieval with Active Moment Discovering
songpipi/amdnet
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Partially relevant video retrieval (PRVR) is a practical yet challenging task in text-to-video retrieval, where videos are untrimmed and contain much background content.
