Awesome-World-Model and World-Models-Autonomous-Driving-Survey
These are competitors—both are curated survey repositories collecting academic papers on world models for autonomous driving, serving the same discovery and reference purpose with overlapping scope.
About Awesome-World-Model
LMD0311/Awesome-World-Model
Collect some World Models for Autonomous Driving (and Robotic, etc.) papers.
This project compiles and tracks research papers on 'World Models' for autonomous driving and robotics. It provides a curated list of academic literature, surveys, and workshop information related to AI models that predict how the world behaves. Anyone researching or developing AI for self-driving cars or advanced robotics would find this useful for staying current with the latest advancements.
About World-Models-Autonomous-Driving-Survey
HaoranZhuExplorer/World-Models-Autonomous-Driving-Survey
A curated list of world models for autonomous driving.
This list compiles research papers focused on "world models" for autonomous driving, which are AI systems that learn to predict how the world around a self-driving car will behave. It helps researchers and engineers in autonomous vehicle development stay current with the latest advancements in predicting driving environments. You'll find a curated collection of papers, including what data they use (like LiDAR or visual inputs) and what they produce (like future occupancy predictions or driving behaviors).
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work