houqb/SPNet
A PyTorch implementation of a semantic segmentation model using strip pooling for scene parsing.
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This repository implements a CVPR 2020 research paper on semantic segmentation and scene parsing. The core contribution is a strip pooling technique that rethinks spatial pooling by using long narrow kernels instead of traditional square pooling windows. The implementation builds on semseg and PyTorch-Encoding libraries, supports synchronized batch normalization across multiple GPUs, and provides pretrained ResNet50/101 backbones. The model is designed for dense pixel-wise prediction tasks likeADE20K scene parsing.
Frequently asked
- What is houqb/SPNet?
- A PyTorch implementation of a semantic segmentation model using strip pooling for scene parsing.
- Is SPNet open source?
- Yes — houqb/SPNet is open source, released under the MIT license.
- What language is SPNet written in?
- houqb/SPNet is primarily written in Python.
- How popular is SPNet?
- houqb/SPNet has 415 stars on GitHub.
- Where can I find SPNet?
- houqb/SPNet is on GitHub at https://github.com/houqb/SPNet.