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cs.CV2026
Adverse-to-the-eXtreme Panoptic Segmentation: URVIS 2026 Study and Benchmark
Yiting Wang, Nolwenn Peyratout, Tim Brodermann +13
This paper presents the report of the URVIS 2026 challenge on adverse-to-extreme panoptic segmentation. As the first challenge of its kind, it attracted 17 registered participants…
cs.CV2026
AURORA-KITTI: Any-Weather Depth Completion and Denoising in the Wild
Yiting Wang, Tim Brödermann, Hamed Haghighi +4
Robust depth completion is fundamental to real-world 3D scene understanding, yet existing RGB-LiDAR fusion methods degrade significantly under adverse weather, where both camera im…
cs.CV2024
Exploring Generative AI for Sim2Real in Driving Data Synthesis
Haonan Zhao, Yiting Wang, Thomas Bashford-Rogers +2
Datasets are essential for training and testing vehicle perception algorithms. However, the collection and annotation of real-world images is time-consuming and expensive. Driving…