Parallel Attention Network with Sequence Matching for Video Grounding (2021.findings-acl)
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| Challenge: | Existing approaches to video grounding are sensitive to quality of proposals and inefficient because all proposal-query pairs are compared. |
| Approach: | They propose a Parallel Attention Network with Sequence matching to capture selfmodal contexts and cross-modal attentive information between video and text. |
| Outcome: | The proposed approach is superior to state-of-the-art methods on three datasets. |
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