VideoLLaMA 2

An advanced spatio-temporal modeling and audio understanding model for video understanding.

CommonProductVideoVideo UnderstandingSpatio-Temporal Modeling

VideoLLaMA 2 is a large language model optimized for video understanding tasks. It leverages advanced spatio-temporal modeling and audio understanding capabilities to enhance the parsing and comprehension of video content. The model demonstrates exceptional performance in tasks such as multiple-choice video question answering and video captioning.

Supports seamless loading and inference of the base model.
Provides an online demo for users to quickly experience the model's functionalities.
Offers capabilities in video question answering and video captioning.
Provides code for training
evaluation
and model serving.
Supports training and evaluation on custom datasets.
Includes detailed installation and usage guides.

VideoLLaMA 2 is designed for researchers and developers working on tasks requiring efficient video content analysis and understanding
particularly in areas such as video question answering and video captioning.

Researchers use VideoLLaMA 2 to develop automatic video question answering systems.
Content creators leverage the model to generate video captions automatically
improving efficiency.
Enterprises apply VideoLLaMA 2 in video surveillance analysis to enhance event detection and response speed.

First
ensure that you have installed the necessary prerequisites
such as Python
Pytorch
and CUDA.

Visit

VideoLLaMA 2 Visit Over Time

Monthly Visits

494758773

Bounce Rate

37.69%

Page per Visit

5.7

Visit Duration

00:06:29

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