GAIA-2: A Controllable Multi-View Generative World Model for Autonomous Driving

• URL: http://arxiv.org/abs/2503.20523v1
• Date: Wed, 26 Mar 2025 13:11:35 GMT
• Title: GAIA-2: A Controllable Multi-View Generative World Model for Autonomous Driving
• Authors: Lloyd Russell, Anthony Hu, Lorenzo Bertoni, George Fedoseev, Jamie Shotton, Elahe Arani, Gianluca Corrado,
• Abstract summary: GAIA-2 is a latent diffusion world model that unifies capabilities within a single generative framework.<n>GAIA-2 supports controllable video generation conditioned on a rich set of structured inputs.<n>It generates high-resolution,temporally consistent multi-camera videos across geographically diverse driving environments.
• Score: 16.101356013671833
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Generative models offer a scalable and flexible paradigm for simulating complex environments, yet current approaches fall short in addressing the domain-specific requirements of autonomous driving - such as multi-agent interactions, fine-grained control, and multi-camera consistency. We introduce GAIA-2, Generative AI for Autonomy, a latent diffusion world model that unifies these capabilities within a single generative framework. GAIA-2 supports controllable video generation conditioned on a rich set of structured inputs: ego-vehicle dynamics, agent configurations, environmental factors, and road semantics. It generates high-resolution, spatiotemporally consistent multi-camera videos across geographically diverse driving environments (UK, US, Germany). The model integrates both structured conditioning and external latent embeddings (e.g., from a proprietary driving model) to facilitate flexible and semantically grounded scene synthesis. Through this integration, GAIA-2 enables scalable simulation of both common and rare driving scenarios, advancing the use of generative world models as a core tool in the development of autonomous systems. Videos are available at https://wayve.ai/thinking/gaia-2.

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