Summary of Beyond the Frame: Single and Mutilple Video Summarization Method with User-defined Length, by Vahid Ahmadi Kalkhorani et al.
Beyond the Frame: Single and mutilple video summarization method with user-defined length
by Vahid Ahmadi Kalkhorani, Qingquan Zhang, Guanqun Song, Ting Zhu
First submitted to arxiv on: 23 Dec 2023
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Machine Learning (cs.LG)
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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 This paper presents a novel method for video summarization, a crucial technique for reducing the time spent watching long videos. The increasing amount of published video content has made this approach more important than ever. The authors employ various techniques from multimodal audio-visual processing and natural language processing (NLP) to summarize a single or multiple videos into a shorter format. Audio-visual cues can identify significant visual events, while NLP approaches evaluate audio transcripts and extract main sentences (timestamps) and corresponding video frames. The paper combines NLP techniques (extractive and contextual summarizers) with video processing methods to convert long videos into short summaries, allowing users to specify the desired length. The authors also explore concatenating multiple videos into a single summary, facilitating access to key concepts on a given topic. This research has significant potential for further development and demonstrates the importance of video summarization in today’s digital landscape. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps us make longer videos shorter, which is super important because we’re watching more videos than ever before! The authors use special computer techniques to help us pick out the most important parts of a video. They combine two types of methods: one that looks at what people are saying (natural language processing) and another that looks at what’s happening on screen (audio-visual). This combination helps create a shorter version of the original video, which is really helpful if you don’t have time to watch something from start to finish. The authors also show us how we can take multiple videos and turn them into one short summary, making it easy to get the main ideas without watching everything. |
Keywords
* Artificial intelligence * Natural language processing * Nlp * Summarization
