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cs.CV2026

SSC-Priors: Exploring Semantic and Visibility Priors to Boost Lidar Semantic Scene Completion

Tetiana Martyniuk, Jonathan Seele, Alexandre Boulch +3

This paper investigates easy strategies to boost the performance of existing networks for lidar semantic scene completion (SSC) without requiring complex architectural redesigns. T…

cs.CV2026

Pictura: Perspective-View Self-Play at Scale for Driving

Yuan Yin, Elias Ramzi, Marc Lafon +8

Self-play in simulation produces robust driving policies at scale. Demonstrations of such behavior have been made using privileged vectorized observations such as exact poses and v…

cs.CV2026

EditSSC: Toward Editable Semantic Occupancy Scenes with Unconditional Diffusion Models

Fatima Balde, Raoul de Charette, Alexandre Boulch

3D semantic scene generation is crucial for autonomous driving applications, yet most methods rely on complex 3D-specific architectures such as triplane encoders and adapted diffus…

cs.CV2026

Exploring Easy Boosts for Lidar Semantic Scene Completion

Tetiana Martyniuk, Jonathan Seele, Alexandre Boulch +3

This paper investigates "free lunch" strategies to boost the performance of lidar semantic scene completion (SSC) without requiring complex architectural redesigns. We first demons…

cs.CV2026

Vanilla ViT for Automotive Point Cloud Semantic Segmentation

Gilles Puy, Nermin Samet, Alexandre Boulch +3

Plain Transformers have become the de-facto architecture for processing text, audio, image, and video, offering a unified backbone for multimodal learning. However, state-of-the-ar…

cs.CV2026

Driving on Registers

Ellington Kirby, Alexandre Boulch, Yihong Xu +11

We present DrivoR, a simple and efficient transformer-based architecture for end-to-end autonomous driving. Our approach builds on pretrained Vision Transformers (ViTs) and introdu…