VideoCLIP-XL
| Property | Value |
|---|---|
| Authors | Jiapeng Wang, Chengyu Wang, Kunzhe Huang, Jun Huang, Lianwen Jin |
| Release Date | 2024 |
| Paper | arXiv:2410.00741 |
| Model Repository | Hugging Face |
What is VideoCLIP-XL?
VideoCLIP-XL is an innovative video-language model that advances the capabilities of CLIP models in understanding long descriptions of video content. Developed by Alibaba PAI, it represents a significant step forward in bridging the gap between video content and textual descriptions, with a particular focus on handling extended narrative descriptions.
Implementation Details
The model implementation requires a Python environment with PyTorch installed. It can be easily set up using the provided requirements.txt file, making it accessible for researchers and developers working in video understanding tasks.
- Released with VILD dataset and LVDR benchmark
- Includes a new V2 version with enhanced capabilities
- Built on CLIP architecture with specialized modifications for video processing
Core Capabilities
- Extended length description processing for videos
- Advanced video-text alignment
- Robust video content understanding
- Support for complex narrative descriptions
Frequently Asked Questions
Q: What makes this model unique?
VideoCLIP-XL stands out for its specialized ability to handle long-form descriptions of video content, going beyond traditional CLIP models' capabilities. It's specifically designed to understand and process extended narratives about video content, making it particularly valuable for detailed video analysis tasks.
Q: What are the recommended use cases?
The model is particularly well-suited for applications requiring detailed video understanding and description matching, such as video search, content analysis, and automated video captioning. It's especially valuable when dealing with complex, narrative descriptions of video content.
