LMD0311/Awesome-World-Model resource

Health v2 · maintenance only

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Adoption not part of the score

2225 stars · 86 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A curated awesome-list collecting papers on World Models for Autonomous Driving and Robotics, maintained as a supplement to a published survey (arXiv:2502.10498). It tracks, records, and benchmarks recent driving world model methods across video, point cloud, occupancy, latent feature, and traffic map modalities.

Use cases

• find papers on world models for autonomous driving
• survey driving world model methods for a literature review
• track recent research on future scene prediction for self-driving
• compare world model approaches across video, point cloud, and occupancy modalities
• find datasets and metrics for evaluating driving world models
• research world models for robotics and embodied AI

When to choose

• you need a comprehensive, continuously updated bibliography of driving world model papers
• you are writing a literature review or survey on world models for autonomous driving
• you want to benchmark or compare world model methods across modalities

When to avoid

• you need runnable code or a software library rather than a paper list
• you need a single maintained implementation instead of research references
• you are looking for general world model research outside driving and robotics

Facets

learning-resource · maturity active

documentation machine-learning computer-vision autonomous-vehicles artificial-intelligence deep-learning robotics computer-vision awesome-lists cross-platform awesome-list world-models survey paper-collection future-prediction benchmarking

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markdown · JSON · MCP: product_card(name="LMD0311/Awesome-World-Model")