3 citations · 4 across the 7 of their papers we have counts for
7 papers · 1 filter
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…
SAIL: Self-supervised Albedo Estimation from Real Images with a Latent Diffusion Model
Hala Djeghim, Nathan Piasco, Luis Roldão +4
Intrinsic image decomposition aims at separating an image into its underlying albedo and shading components, isolating the base color from lighting effects to enable downstream app…
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…
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…
3D Semantic Scene Completion: a Survey
Luis Roldao, Raoul de Charette, Anne Verroust-Blondet
Semantic Scene Completion (SSC) aims to jointly estimate the complete geometry and semantics of a scene, assuming partial sparse input. In the last years following the multiplicati…
LMSCNet: Lightweight Multiscale 3D Semantic Completion
Luis Roldão, Raoul de Charette, Anne Verroust-Blondet
We introduce a new approach for multiscale 3Dsemantic scene completion from voxelized sparse 3D LiDAR scans. As opposed to the literature, we use a 2D UNet backbone with comprehens…