3 papers
cs.CV2026
HELIOS: From midnight to noon, continuous outdoor urban scene relighting
Hala Djeghim, Nathan Piasco, Luis Roldão +4
Modifying the illumination of driving images is a fundamental challenge, as most datasets are captured at specific times of day. Existing methods rely on synthetic data or paired m…
cs.CV2026
Cyclone: Diffusion Model for Cycle-Consistent Weather Editing from Unpaired Driving Data
Thang-Anh-Quan Nguyen, Moussab Bennehar, Luis Guillermo Roldao Jimenez +5
Reliable perception under diverse weather conditions remains a major challenge for autonomous driving systems. A common strategy to improve robustness is either to synthesize adver…
cs.CV2026
DrivingVoxels: Compositional Sparse Voxel Rasterization for Dynamic Driving Scene Reconstruction
Tania Aguirre, Luis Roldão, Moussab Bennehar +4
Reconstructing dynamic urban scenes remains challenging due to the unbounded nature of driving environments and the presence of multiple dynamic objects. Currently, potentially fas…