AI RESEARCH
Heuristic Style Transfer for Real-Time, Efficient Weather Attribute Detection
arXiv CS.CV
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ArXi:2604.13947v1 Announce Type: new We present lightweight and efficient architectures to detect weather conditions from RGB images, predicting the weather type (sunny, rain, snow, fog) and 11 complementary attributes such as intensity, visibility, and ground condition, for a total of 53 classes across the tasks. This work examines to what extent weather conditions manifest as variations in visual style.