ViSnow: Snow-covered Urban Roads Dataset for Computer Vision Applications

We present ViSnow: a large image dataset for snow-covered roads in an urban setting. The dataset includes an extensive collection of images from traffic surveillance cameras installed in Montreal, Quebec, Canada, during the winters of 2022 and 2023. ViSnow dataset aims to enable computer vision applications in intelligent transportation and winter road maintenance. ViSnow comprises 294,000 images describing various settings spanning day and night periods, different weather conditions (snow, rain, clear), and multiple urban areas (residential, commercial, industrial). We attach a metadata JSON file recording the timestamp and weather data to each image to provide more contextual information. ViSnow images are annotated to describe four snow cover classes: “clear surface”, “light-covered surface”, “medium-to-heavy-covered surface”, and “plowed surface”, matching possible snow removal operations.