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cs.CV2026

How Far Can 5,500 Hours of Driving Take You? A Scaling Law Analysis of Video Diffusion Models

Victor Besnier, Anh-Quan Cao, Elias Ramzi +5

Video generation for autonomous driving cannot follow the web-scale route: driving data is expensive to collect, bound by privacy requirements, and cannot be scraped at will, so mo…

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.CV2025

Franca: Nested Matryoshka Clustering for Scalable Visual Representation Learning

Shashanka Venkataramanan, Valentinos Pariza, Mohammadreza Salehi +5

We present Franca (pronounced Fran-ka): free one; the first fully open-source (data, code, weights) vision foundation model that matches and in many cases surpasses the performance…

cs.CV2025

VaViM and VaVAM: Autonomous Driving through Video Generative Modeling

Florent Bartoccioni, Elias Ramzi, Victor Besnier +14

We explore the potential of large-scale generative video models for autonomous driving, introducing an open-source auto-regressive video model (VaViM) and its companion video-actio…

cs.CV2024

LLM-wrapper: Black-Box Semantic-Aware Adaptation of Vision-Language Models for Referring Expression Comprehension

Amaia Cardiel, Eloi Zablocki, Elias Ramzi +2

Vision Language Models (VLMs) have demonstrated remarkable capabilities in various open-vocabulary tasks, yet their zero-shot performance lags behind task-specific fine-tuned model…