RegDB-C* is an evaluation set that consists of algorithmically generated corruptions applied to the RegDB test-set, and especially to both the visible and the thermal data. In comparison with the RegDB-C dataset proposed by Chen et al. in "Benchmarks for Corruption Invariant Person Re-identification" paper, our dataset is used in a multimodal manner and do not consider visible data corruptions only. Used corruptions are globally the same; Noise: Gaussian, shot, impulse, and speckle; Blur: defocus, frosted glass, motion, zoom, and Gaussian; Weather: snow, frost, fog, brightness, spatter, and rain; Digital: contrast, elastic, pixel, JPEG compression, and saturate. However, corruptions are adapted to respect the thermal modality encoding, and brightness is not used to corrupt the thermal data. Five severity levels are considered per corruption.