3 citations · 3 across the 3 of their papers we have counts for
3 papers
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…
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…
Benchmarking the Robustness of Panoptic Segmentation for Automated Driving
Yiting Wang, Haonan Zhao, Daniel Gummadi +3
Precise situational awareness is required for the safe decision-making of assisted and automated driving (AAD) functions. Panoptic segmentation is a promising perception technique…