nv-tlabs/GSCNN
A PyTorch implementation of Gated-SCNN, a deep learning model for semantic image segmentation published at ICCV 2019.
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Gated Shape CNN (GSCNN) is a semantic segmentation architecture that incorporates shape information through gated convolutions. It achieves state-of-the-art results on segmentation benchmarks by jointly learning class predictions and boundary detection. The model is implemented in PyTorch and was developed by NVIDIA’s Toronto AI Lab.
Frequently asked
- What is nv-tlabs/GSCNN?
- A PyTorch implementation of Gated-SCNN, a deep learning model for semantic image segmentation published at ICCV 2019.
- Is GSCNN open source?
- Yes — nv-tlabs/GSCNN is an open-source project tracked on heatdrop.
- What language is GSCNN written in?
- nv-tlabs/GSCNN is primarily written in Python.
- How popular is GSCNN?
- nv-tlabs/GSCNN has 938 stars on GitHub.
- Where can I find GSCNN?
- nv-tlabs/GSCNN is on GitHub at https://github.com/nv-tlabs/GSCNN.