How to Build World Models|ECCV'26

About

World models are frameworks that learn the internal representation of the world and are able to predict its future states. World modeling is not a new concept, however, in recent years due to significant improvement in computational power and abundance of available data, building effective world models is becoming a reality. World models are universally regarded as the next frontier in AI and a path to achieving human-level intelligence.

This workshop brings researchers from academia and industry working at the intersection of computer vision, robotics, language, and generative modeling to explore what distinguishes world models from other predictive systems, such as video generation models,whether existing world models are sufficient for embodied AI, which modalities a good world model should posses, what data and learning schemas are best suited for training world models, and how to effectively integrate world models within embodied AI.

Topics of interest

World models integration into embodied AI systems
Data generation and training regiments for world models
Simulation, imagination, and generative latent models
Learned world models for planning and control
Evaluation protocols and benchmarking
Scaling world models across different domains

Schedule

Speakers

Call for Papers

We invite original research contributions on world modeling and embodied AI, aligned with any of the topics of interest of the workshop. The submitted work is limited to 14 pages (excluding references) and should follow the official ECCV'26 guidelines. The submissions are evaluated based on the novelty, relevance to the workshop topics, and significance. The accepted papers will be included in ECCV workshop proceedings.