mlsanityData to 14 Oct 2026

SSSegmenation: An Open Source Supervised Semantic Segmentation Toolbox Based on PyTorch

arXiv 2305.17091 ↗First posted 26 May 2023cs.CVcited by 4

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Abstract (arXiv)

This paper presents SSSegmenation, which is an open source supervised semantic image segmentation toolbox based on PyTorch. The design of this toolbox is motivated by MMSegmentation while it is easier to use because of fewer dependencies and achieves superior segmentation performance under a comparable training and testing setup. Moreover, the toolbox also provides plenty of trained weights for popular and contemporary semantic segmentation methods, including Deeplab, PSPNet, OCRNet, MaskFormer, etc. We expect that this toolbox can contribute to the future development of semantic segmentation. Codes and model zoos are available at hrefhttps://github.com/SegmentationBLWX/sssegmentation/SSSegmenation.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 47 of its 58 references that are in the map. First posted on arXiv 26 May 2023.

Builds on

47 of 58 references.

References · 47

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35 more
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Built on by

Cited by year

Citing papers per year: 2023: 1; 2024: 2; 2025: 1.

4 papers.

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