Summary of Qd-vmr: Query Debiasing with Contextual Understanding Enhancement For Video Moment Retrieval, by Chenghua Gao et al.
QD-VMR: Query Debiasing with Contextual Understanding Enhancement for Video Moment Retrieval
by Chenghua Gao, Min Li, Jianshuo Liu, Junxing Ren, Lin Chen, Haoyu Liu, Bo Meng, Jitao Fu, Wenwen Su
First submitted to arxiv on: 23 Aug 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel approach for Video Moment Retrieval (VMR) is introduced in this paper, which aims to retrieve relevant moments from an untrimmed video based on a given query. The proposed model, called QD-VMR, combines cross-modal interaction and contextual understanding to enhance the accuracy of VMR. This is achieved by leveraging a Global Partial Aligner module for video clip and query features alignment, as well as video-query contrastive learning. Additionally, a Query Debiasing Module is employed to obtain debiased query features efficiently, while a Visual Enhancement module refines video features related to the query. The DETR structure is used to predict possible target video moments. Experimental results on three benchmark datasets demonstrate QD-VMR’s state-of-the-art performance and potential for improving VMR accuracy. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Video Moment Retrieval (VMR) helps find important parts in a long video that match what you’re asking about. This task is hard because videos can be very long, and it’s not always easy to understand what someone means when they ask a question. To make this job easier, researchers created a new model called QD-VMR. It uses two main ideas: one helps understand how video clips relate to questions, and the other adjusts the question so it matches better with the video. This makes the model really good at finding important moments in videos. |
Keywords
» Artificial intelligence » Alignment
