LongVU
Spatiotemporal adaptive compression model for long video language understanding
Product Details
LongVU is an innovative long video language understanding model that reduces the number of video tags through a spatiotemporal adaptive compression mechanism while retaining visual details in long videos. The importance of this technology lies in its ability to process a large number of video frames with only a small loss of visual information within the limited context length, significantly improving the ability to understand and analyze long video content. LongVU outperforms existing methods on multiple video understanding benchmarks, especially on the task of understanding hour-long videos. Additionally, LongVU is able to efficiently scale to smaller model sizes while maintaining state-of-the-art video understanding performance.
Main Features
How to Use
Target Users
LongVU's target audience is researchers and developers in the field of video content analysis and understanding, especially professionals who need to process long video content and want to achieve efficient video understanding under limited computing resources. In addition, LongVU provides an advanced solution for enterprises and institutions that want to apply the latest artificial intelligence technology in the field of video analysis.
Examples
When users ask for video content details, LongVU can provide detailed video scene descriptions.
Users ask questions about specific actions in the video, and LongVU can accurately identify and answer them.
Users need to know the moving direction of specific objects in the video, and LongVU can accurately identify and describe object movement.
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