Short Video

Short-form video research centers on understanding and leveraging the unique characteristics of these ubiquitous, brief video clips, focusing on improving recommendation systems, content creation, and analysis. Current research employs various deep learning models, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), transformers, and large language models (LLMs), to address challenges such as video summarization, fake news detection, user interest modeling, and quality assessment. These advancements have significant implications for personalized content delivery, combating misinformation, and enhancing video understanding across diverse applications, from social media platforms to video search engines. The development of large-scale, annotated datasets is also a key focus, enabling the training and evaluation of increasingly sophisticated models.