Summary of Query-centric Audio-visual Cognition Network For Moment Retrieval, Segmentation and Step-captioning, by Yunbin Tu et al.
Query-centric Audio-Visual Cognition Network for Moment Retrieval, Segmentation and Step-Captioning
by Yunbin Tu, Liang Li, Li Su, Qingming Huang
First submitted to arxiv on: 18 Dec 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Computation and Language (cs.CL)
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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 The paper proposes a novel approach to video content retrieval, moment segmentation, and step-captioning using a multi-task learning paradigm with a pre-trained CLIP-based model as a feature extractor. The work aims to improve upon previous methods by incorporating hierarchies and association relations across modalities to better understand user-preferred content. A query-centric audio-visual cognition (QUAG) network is designed to construct a reliable multi-modal representation for the three tasks, leveraging modality-synergistic perception and query-centric cognition. The paper achieves state-of-the-art results on the HIREST dataset and demonstrates good generalization on query-based video summarization. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary A new way to understand videos has been discovered! Video is a popular format online, but it’s hard for computers to “understand” what’s happening in them. This paper tries to solve this problem by creating a special system that can look at both the pictures and sounds in a video together. It uses a clever trick called multi-task learning to make the system better at understanding what people like about certain videos. The result is a new way to organize and summarize videos that is more accurate than before. |
Keywords
» Artificial intelligence » Generalization » Multi modal » Multi task » Summarization
