CoTracker3
| Property | Value |
|---|---|
| Author | Facebook Research |
| Paper | arXiv:2410.11831 |
| Model Type | Transformer-based Point Tracker |
| Repository | https://huggingface.co/facebook/cotracker3 |
What is cotracker3?
CoTracker3 is an advanced transformer-based model designed for point tracking in videos. Developed by Facebook Research, it represents a significant improvement in video point tracking technology by implementing pseudo-labelling on real videos. The model offers both offline and online processing capabilities, making it versatile for various applications requiring precise point tracking.
Implementation Details
The model can be implemented in two modes: offline and online. It utilizes PyTorch and can process videos on CUDA-enabled devices. The implementation supports both grid-based tracking and manual point selection, with the ability to track multiple points simultaneously across video frames.
- Supports both offline and online processing modes
- Built on PyTorch framework
- Provides CUDA acceleration support
- Flexible grid size configuration
- Memory-efficient online processing for longer videos
Core Capabilities
- Track any pixel in a video sequence
- Process quasi-dense set of pixels together
- Support for manual point selection
- Grid-based sampling on any video frame
- Real-time processing capability in online mode
Frequently Asked Questions
Q: What makes this model unique?
CoTracker3 stands out for its improved approach to point tracking using pseudo-labelling on real videos, offering both simplicity and enhanced performance. It combines the benefits of optical flow with transformer-based architecture, allowing for more accurate and efficient point tracking.
Q: What are the recommended use cases?
The model is ideal for applications requiring precise point tracking in videos, such as motion analysis, video editing, computer vision research, and real-time tracking applications. Its dual-mode operation (online/offline) makes it suitable for both post-processing and real-time tracking scenarios.
