Summary of Verified: a Video Corpus Moment Retrieval Benchmark For Fine-grained Video Understanding, by Houlun Chen et al.
VERIFIED: A Video Corpus Moment Retrieval Benchmark for Fine-Grained Video Understanding
by Houlun Chen, Xin Wang, Hong Chen, Zeyang Zhang, Wei Feng, Bin Huang, Jia Jia, Wenwu Zhu
First submitted to arxiv on: 11 Oct 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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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 medium-difficulty summary of the abstract would explain that existing Video Corpus Moment Retrieval (VCMR) approaches are limited to coarse-grained understanding, making it challenging to precisely localize video moments when given fine-grained queries. To address this limitation, researchers propose a new fine-grained VCMR benchmark requiring methods to locate the best-matched moment from a corpus with other partially matched candidates. The authors also introduce VERIFIED, an automatic pipeline for generating high-quality annotations of video captions using large language and multimodal models. They then evaluate several state-of-the-art VCMR models on this new dataset, revealing significant scope for improving fine-grained video understanding in the field. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about creating a more challenging task for machines to understand videos accurately. Right now, most machines are only good at understanding big chunks of videos, but they struggle with finding specific moments within those chunks. The researchers created a new way of labeling video captions that helps machines learn to find these specific moments. They tested different machine learning models on this new dataset and found that there is still much room for improvement in accurately understanding short moments within videos. |
Keywords
» Artificial intelligence » Machine learning
