Large language models (LLMs) have revolutionized video-based computer vision
applications, including action recognition, anomaly detection, and video summarization …

This paper aims to improve the performance of video multimodal large language models
(MLLM) via long and rich context (LRC) modeling. As a result, we develop a new version of …

In this paper, we propose VideoLLaMA3, a more advanced multimodal foundation model for
image and video understanding. The core design philosophy of VideoLLaMA3 is vision …

Visual tokenization via auto-encoding empowers state-of-the-art image and video
generative models by compressing pixels into a latent space. Although scaling Transformer …

Despite significant advancements in video large multimodal models (video-LMMs),
achieving effective temporal grounding in long-form videos remains a challenge for existing …

With the rapid iteration of Multi-modality Large Language Models (MLLMs) and the evolving
demands of the field, the number of benchmarks produced annually has surged into the …