Awesome-World-Model

Why we included this project

This list is a good first stop for anyone working on autonomous driving or embodied robotics who keeps losing track of the world-model papers scattered across arXiv. It collects recent methods that predict future driving scenes and feed end-to-end perception and planning, and it records benchmark results alongside the papers, which makes comparing approaches or picking a baseline to reproduce much less painful. The maintainers also wrote an accompanying survey, so newcomers can read the field in order instead of jumping between random preprints. Since pull requests and issues are welcome, the list stays reasonably current, and the contribution guidelines lower the barrier for adding a paper you think is missing. For scoping a research project or drafting a related-works section, this saves real time.