Organic waste management is a crucial component of a circular economy, which prioritizes reducing waste through the reuse and recycling of products and materials. It is a tedious and complicated task, largely accomplished through manual labor. We introduce a novel ‘in-the-wild’ multimodal image dataset of 15-band NIR multi-spectral and single band thermal images of bulk food waste in an industrial setting. The dataset showcases a number of complex computer vision problems that are unavoidable constraints in this setting. Benchmarking against different computer vision algorithms is performed to highlight these challenges. The key issues and their place in robotic waste processing for industrial applications, and grand challenge objectives are discussed.
Vestal, M., Ireland, J., Wang, X., Subramanian, R. and Herath, D., 2025, October. ICMI’25 Grand Challenge: A Thermal and Spectral Multimodal Image Dataset for Contaminant Detection in Industrial Organic Food Waste. In Proceedings of the 27th International Conference on Multimodal Interaction (pp. 797-802).