X-CLIP Large Patch14
| Property | Value |
|---|---|
| Parameter Count | 576M |
| License | MIT |
| Paper | View Paper |
| Top-1 Accuracy | 87.1% |
| Training Dataset | Kinetics-400 |
What is xclip-large-patch14?
X-CLIP large-patch14 is a sophisticated video-language understanding model that extends the capabilities of CLIP for processing video content. Developed by Microsoft, this model represents a significant advancement in video classification and video-text retrieval tasks, utilizing a patch resolution of 14 and processing 8 frames per video at 224x224 resolution.
Implementation Details
The model implements a contrastive learning approach for video-language understanding, trained on the Kinetics-400 dataset. It processes video input through a specialized architecture that handles both spatial and temporal dimensions of video data.
- Achieves 87.1% top-1 accuracy and 97.6% top-5 accuracy
- Processes 8 frames per video sequence
- Uses 224x224 resolution for frame analysis
- Implements patch-based processing with 14x14 patches
Core Capabilities
- Zero-shot video classification
- Few-shot learning capabilities
- Video-text retrieval
- Fully supervised video classification
- General video-language understanding
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its minimal yet effective extension of CLIP architecture for video understanding, achieving high accuracy while maintaining practical efficiency. The large-patch14 variant offers superior performance with 87.1% top-1 accuracy on Kinetics-400.
Q: What are the recommended use cases?
The model is ideal for tasks involving video classification, video-text matching, and retrieval applications. It's particularly effective for scenarios requiring understanding of temporal relationships in video content and matching video content with textual descriptions.
