From the 1 of 9 linked papers with an AI index.
9 papers
Cyclone: Diffusion Model for Cycle-Consistent Weather Editing from Unpaired Driving Data
Thang-Anh-Quan Nguyen, Moussab Bennehar, Luis Guillermo Roldao Jimenez +5
Cyclone is a latent diffusion framework that edits weather conditions in driving images without paired data, using cycle-consistent constraints and image‑text knowledge to produce…
LESV: Language Embedded Sparse Voxel Fusion for Open-Vocabulary 3D Scene Understanding
Fusang Wang, Nathan Piasco, Moussab Bennehar +3
Recent advancements in open-vocabulary 3D scene understanding heavily rely on 3D Gaussian Splatting (3DGS) to register vision-language features into 3D space. However, we identify…
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…
SEM-ROVER: Semantic Voxel-Guided Diffusion for Large-Scale Driving Scene Generation
Hiba Dahmani, Nathan Piasco, Moussab Bennehar +5
Scalable generation of outdoor driving scenes requires 3D representations that remain consistent across multiple viewpoints and scale to large areas. Existing solutions either rely…
Pointmap-Conditioned Diffusion for Consistent Novel View Synthesis
Thang-Anh-Quan Nguyen, Nathan Piasco, Luis Roldão +5
Synthesizing extrapolated views remains a difficult task, especially in urban driving scenes, where the only reliable sources of data are limited RGB captures and sparse LiDAR poin…
J-NeuS: Joint field optimization for Neural Surface reconstruction in urban scenes with limited image overlap
Fusang Wang, Hala Djeghim, Nathan Piasco +6
Reconstructing the surrounding surface geometry from recorded driving sequences poses a significant challenge due to the limited image overlap and complex topology of urban environ…