The Large Vision-Language Model (LVLM) has enhanced the performance of various
downstream tasks in visual-language understanding. Most existing approaches encode …

This work proposes TimeChat a time-sensitive multimodal large language model specifically
designed for long video understanding. Our model incorporates two key architectural …

With the burgeoning growth of online video platforms and the escalating volume of video
content, the demand for proficient video understanding tools has intensified markedly. Given …

Video-based large language models (Video-LLMs) have been recently introduced, targeting
both fundamental improvements in perception and comprehension, and a diverse range of …

Vision-language pre-training has significantly elevated performance across a wide range of
image-language applications. Yet, the pre-training process for video-related tasks demands …

We present the ShareGPT4Video series, aiming to facilitate the video understanding of large
video-language models (LVLMs) and the video generation of text-to-video models (T2VMs) …

This paper presents VideoStreaming, an advanced vision-language large model (VLLM) for
video understanding, that capably understands arbitrary-length video with a constant …

While recent progress in multimodal large language models tackles various modality tasks,
they posses limited integration capabilities for complex multi-modality tasks, consequently …

Large Language Models (LLMs) have showcased impressive capabilities in text
comprehension and generation, prompting research efforts towards video LLMs to facilitate …

Video sequences offer valuable temporal information, but existing large multimodal models
(LMMs) fall short in understanding extremely long videos. Many works address this by …