Video analytics capabilities
- Zero Sample Video Classification: categorize video content without prior training
- Text-Video Search: Searching for relevant content in a video library based on natural language descriptions
- Video Content Summary: automatically generate text descriptions of video content
- motion recognition: Recognize specific behaviors or actions in a video
Zero Sample Video Classification Process
- Upload Video: Support for common video formats
- Keyframe extraction: The model automatically selects a representative screen
- multimodal encoding: Analyze visual and audio information
- semantic association: Aligning video content with open domain text descriptions
- categorized output: return the most likely content category
Technical characteristics
InternVL uses dynamic sampling and attention mechanisms to process temporal information in videos to support long video understanding. The model achieves zero-sample capability through cross-modal comparison learning, which can be directly applied to new domains without fine-tuning.
application scenario
It is suitable for a variety of application scenarios such as video content auditing, media asset management, educational video retrieval, etc., and significantly reduces the realization threshold of video analytics.
This answer comes from the articleInternVL: Open Source Multimodal Large Model with Image, Video and Text Processing SupportThe
May not be reproduced without permission:AI productivity tools " What types of video analysis tasks does InternVL support? How to perform zero-sample video classification?
