6 papers
DriveCtrl: Conditioned Sim-to-Real Driving Video Generation
Haonan Zhao, Yiting Wang, Jingkun Chen +3
Large-scale labelled driving video data is essential for training autonomous driving systems. Although simulation offers scalable and fully annotated data, the domain gap between s…
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…
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…
CapHDR2IR: Caption-Driven Transfer from Visible Light to Infrared Domain
Jingchao Peng, Thomas Bashford-Rogers, Zhuang Shao +4
Infrared (IR) imaging offers advantages in several fields due to its unique ability of capturing content in extreme light conditions. However, the demanding hardware requirements o…
Luminance Component Analysis for Exposure Correction
Jingchao Peng, Thomas Bashford-Rogers, Jingkun Chen +3
Exposure correction methods aim to adjust the luminance while maintaining other luminance-unrelated information. However, current exposure correction methods have difficulty in ful…
A Unified Generative Framework for Realistic Lidar Simulation in Autonomous Driving Systems
Hamed Haghighi, Mehrdad Dianati, Valentina Donzella +1
Simulation models for perception sensors are integral components of automotive simulators used for the virtual Verification and Validation (V\&V) of Autonomous Driving Systems (ADS…