MatAnyone 2: Scaling Video Matting via a Learned Quality Evaluator
Paper • 2512.11782 • Published • 2
MatAnyone 2 is a practical human video matting framework that preserves fine details by avoiding segmentation-like boundaries, while also shows enhanced robustness under challenging real-world conditions.
🎥 For more visual results, go checkout our project page
you can run the following commands to get started and start working with the model
pip install -qqU git+https://github.com/pq-yang/MatAnyone2.git
from matanyone2 import MatAnyone2, InferenceCore
model = MatAnyone2.from_pretrained("PeiqingYang/MatAnyone2")
processor = InferenceCore(model,device="cuda:0")
# inference
processor.process_video(input_path="inputs/video/test-sample2.mp4",
mask_path="inputs/mask/test-sample2.png",
output_path="results")