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Found 2 papers, 1 papers with code
Pseudo Pixel-level Labeling for Images with Evolving Content
Annotating images for semantic segmentation requires intense manual labor and is a time-consuming and expensive task especially for domains with a scarcity of experts, such as Forensic Anthropology.
SLRNet: Semi-Supervised Semantic Segmentation Via Label Reuse for Human Decomposition Images
We evaluate our method on a large dataset of human decomposition images and find that our method, while conceptually simple, outperforms state-of-the-art consistency and pseudo-labeling-based methods for the segmentation of this dataset.
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