Survey of video understanding with Large Language Models
Survey of video understanding with Large Language Models
Video Understanding with Large Language Models: A Survey
arXiv paper abstract https://arxiv.org/abs/2312.17432
arXiv PDF paper https://arxiv.org/pdf/2312.17432.pdf
Project page https://github.com/yunlong10/Awesome-LLMs-for-Video-Understanding
… this survey provides a detailed overview of the recent advancements in video understanding harnessing the power of LLMs (Vid-LLMs).
The emergent capabilities of Vid-LLMs are surprisingly advanced, particularly their ability for open-ended spatial-temporal reasoning combined with commonsense knowledge
… examine the unique characteristics and capabilities of Vid-LLMs, categorizing the approaches into four main types: LLM-based Video Agents, Vid-LLMs Pretraining, Vid-LLMs Instruction Tuning, and Hybrid Methods.
… presents a comprehensive study of the tasks and datasets for Vid-LLMs, along with the methodologies employed for evaluation.
…explores the expansive applications of Vid-LLMs across various domains, thereby showcasing their remarkable scalability and versatility in addressing challenges in real-world video understanding.
… summarizes the limitations of existing Vid-LLMs and the directions for future research …
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