On the Influence of Shape, Texture and Color for Learning Semantic Segmentation - Texture Cue
Creators
Description
This work is supported by the German Federal Ministry for Economic Affairs and Climate Action within the project “KI Delta Learning”, grant no. 19A19013Q. We acknowledge support through the junior research group project “UnrEAL” by the German Federal Ministry of Research, Technology and Space (BMFTR), grant no. 01IS22069. The research of us leading to these results is funded by the German Federal Ministry for Economic Affairs and Energy within the project “NXT GEN AI METHODS – Generative Methoden für Perzeption, Prädiktion und Planung” grant no. 19A23014Q. We thank all consortia for the successful cooperation.
Due to Zenodo's upload limit of 50GB, the creators have compressed the images compared to those used in the paper, resulting in a slight visual loss of image quality. If you would like to access the original dataset with the full image quality, please reach out to the contact person. We can then work together to find a suitable solution for providing the original dataset.
Files
Texture_dataset.zip
Files
(12.6 GB)
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md5:7c904268465dc4614790928b5ee1df59
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6.6 kB | Download |
md5:a1a662a6a65052b9c42e541d3749cee3
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12.6 GB | Preview Download |
Additional details
Identifiers
- arXiv
- arXiv:2410.14878
Dates
- Available
-
2025-08-25
Software
- Repository URL
- https://github.com/a-muetze/influence-of-shape-texture-color-learning-semseg
- Programming language
- Python