Papers with long video temporal grounding
CONE: An Efficient COarse-to-fiNE Alignment Framework for Long Video Temporal Grounding (2023.acl-long)
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Zhijian Hou, Wanjun Zhong, Lei Ji, Difei Gao, Kun Yan, W.k. Chan, Chong-Wah Ngo, Mike Zheng Shou, Nan Duan
| Challenge: | Existing work on video temporal grounding for long videos is limited by existing datasets. |
| Approach: | They propose a query-guided window selection strategy and a coarse-to-fine mechanism to speed up inference for long videos. |
| Outcome: | The proposed framework accelerates inference time by 2x on Ego4D-NLQ and 15x on MAD while keeping SOTA results. |