Summary of Vtg-gpt: Tuning-free Zero-shot Video Temporal Grounding with Gpt, by Yifang Xu et al.
VTG-GPT: Tuning-Free Zero-Shot Video Temporal Grounding with GPT
by Yifang Xu, Yunzhuo Sun, Zien Xie, Benxiang Zhai, Sidan Du
First submitted to arxiv on: 4 Mar 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 In this paper, the authors propose a GPT-based method called VTG-GPT for zero-shot video temporal grounding (VTG) without training or fine-tuning. The proposed approach addresses two challenges in existing VTG models: human bias introduced by annotated video-text pairs and computational costs. To reduce prejudice in queries, the authors employ Baichuan2 to generate debiased queries. They also apply MiniGPT-v2 to transform visual content into more precise captions. The paper presents a proposal generator and post-processing to produce accurate segments from debiased queries and image captions. The experimental results demonstrate that VTG-GPT outperforms state-of-the-art (SOTA) methods in zero-shot settings and achieves competitive performance comparable to supervised methods. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper creates a new way for computers to understand specific moments in videos based on what we say. Usually, these systems need lots of practice data and can be biased by the words used to describe them. The authors developed a system that doesn’t require this training and can still accurately identify moments in videos. They also made sure the system is fair and doesn’t favor certain words over others. This new approach works really well and is even as good as systems that have been trained with lots of data. |
Keywords
» Artificial intelligence » Fine tuning » Gpt » Grounding » Supervised » Zero shot
