Adverse weather and illumination conditions (e.g. fog, rain, snow, ice, low light, nighttime, glare and shadows) create visibility problems for the sensors that power automated systems. Many outdoor applications such as autonomous cars and surveillance systems are required to operate smoothly in the frequent scenarios of bad weather. While rapid progress is being made in this direction, the performance of current vision algorithms is still mainly benchmarked under clear weather conditions (good weather, favorable lighting). Even the top-performing state-of-the-art algorithms undergo a severe performance degradation under adverse conditions. The aim of this workshop is to promote research into the design of robust vision algorithms for adverse weather and illumination conditions.
Call for papers: IJCV Special Issue on “Computer Vision for All Seasons: Adverse Weather and Illumination Conditions”. Deadline is 10 Dec. 2019. Check out here for more details.
University of Oxford
Vishal M. Patel
Johns Hopkins Uni.