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nnMNet: Baseline for Martian Terrain Semantic Segmentation

arXiv · AI, language, vision and robotics · article · Aug 30, 2026 · UTC

Semantic segmentation is a crucial task for understanding Mars, the most Earth-like planet in our solar system. However, it is challenging because the Martian surface is highly unstructured and complex, making accurate pixel-level prediction and fine-grained annotation difficult. Recent advancements in deep learning have introduced numerous methods and datasets to address these challenges. Nevertheless, the field lacks a robust, publicly available, and reproducible baseline, as well as a unified benchmark to facilitate fair evaluations. In this work, we present nnMNet, a new baseline model des

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First collected: 2026-09-21T07:31:56.984Z. This is not the publication date.