SegAnyMo: Segment Any Motion in Videos
SegAnyMo is a cutting-edge tool designed for motion segmentation in videos, developed for the CVPR 2025 conference. This repository provides the code to segment any motion in videos using advanced techniques such as motion encoding and semantic information decoupling.
Key Features:
- Motion Segmentation: Efficiently segments moving objects in video sequences.
- Deep Learning Framework: Built on PyTorch, ensuring high performance and flexibility.
- Preprocessing Support: Includes tools for data preprocessing, depth estimation, and feature extraction.
- Model Training: Provides scripts for training on custom datasets, enhancing adaptability.
- Evaluation Tools: Offers evaluation scripts for assessing segmentation performance on standard datasets.
Benefits:
- User-Friendly: Simple setup and usage instructions make it accessible for researchers and developers.
- High Accuracy: Leverages state-of-the-art models to achieve precise motion segmentation.
- Open Source: Available on GitHub, encouraging collaboration and contributions from the community.
Highlights:
- Developed by a team of researchers from UC Berkeley and Peking University.
- Supports various input formats, including image sequences and video files.
- Optimized for efficiency with options to accelerate data processing.
Explore the full potential of motion segmentation with SegAnyMo!