foolwood/SiamMask
SiamMask is a real-time object tracking and video object segmentation framework published at CVPR 2019 and TPAMI 2023.
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SiamMask provides a unified approach for fast online object tracking and segmentation using deep learning. The framework uses a Siamese network architecture with a mask branch for segmentation, enabling simultaneous tracking and segmentation in video. It includes both training and inference code implemented in PyTorch, with models designed for real-time performance on visual tracking benchmarks.
Frequently asked
- What is foolwood/SiamMask?
- SiamMask is a real-time object tracking and video object segmentation framework published at CVPR 2019 and TPAMI 2023.
- Is SiamMask open source?
- Yes — foolwood/SiamMask is open source, released under the MIT license.
- What language is SiamMask written in?
- foolwood/SiamMask is primarily written in Python.
- How popular is SiamMask?
- foolwood/SiamMask has 3.5k stars on GitHub.
- Where can I find SiamMask?
- foolwood/SiamMask is on GitHub at https://github.com/foolwood/SiamMask.