Awesome
<div align="center"> <img src="./docs/logo.png" width="600"/> </div> <br />Documents: https://cssegmentation.readthedocs.io/en/latest/
Introduction
CSSegmentation: An Open Source Continual Semantic Segmentation Toolbox Based on PyTorch. You can star this repository to keep track of the project if it's helpful for you, thank you for your support.
Major Features
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High Performance
The performance of re-implemented CSS algorithms is better than or comparable to the original paper.
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Modular Design and Unified Benchmark
Various CSS methods are unified into several specific modules. Benefiting from this design, CSSegmentation can integrate a great deal of popular and contemporary continual semantic segmentation frameworks and then, train and test them on unified benchmarks.
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Fewer Dependencies
CSSegmentation tries its best to avoid introducing more dependencies when reproducing novel continual semantic segmentation approaches.
Benchmark and Model Zoo
Supported Encoder
Encoder | Model Zoo | Paper Link | Code Snippet |
---|---|---|---|
ResNet | click | CVPR 2016 | click |
Supported Decoder
Decoder | Model Zoo | Paper Link | Code Snippet |
---|---|---|---|
Deeplabv3 | click | ArXiv 2017 | click |
Supported Runner
Supported Datasets
Dataset | Project Link | Paper Link | Code Snippet |
---|---|---|---|
ADE20k | Click | CVPR 2017 | Click |
PASCAL VOC | Click | IJCV 2010 | Click |
Citation
If you use this framework in your research, please cite this project:
@misc{csseg2023,
author = {Zhenchao Jin},
title = {CSSegmentation: An Open Source Continual Semantic Segmentation Toolbox Based on PyTorch},
year = {2023},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/SegmentationBLWX/cssegmentation}},
}