ad-generative-models
OfficialModel and synthesize autonomous driving scenes with advanced generative techniques.
Education & Research#diffusion models#world models#autonomous driving#generative models#3D Gaussian Splatting#sensor data generation
AuthorRoboSafe-Lab
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill provides advanced tools for generating and synthesizing driving scenes for autonomous driving research, addressing the need for diverse and realistic data without extensive real-world collection.
Core Features & Use Cases
- World Models: Learn to predict future states of the driving environment.
- Diffusion Models: Generate diverse, realistic future trajectories and scenes.
- 3D Gaussian Splatting: Create and manipulate 3D representations of driving scenes.
- Sensor Data Generation: Synthesize realistic sensor data like LiDAR and radar for simulation.
- Use Case: Generate novel driving scenarios with specific vehicle behavior, traffic patterns, or environmental conditions to evaluate autonomous driving systems.
Quick Start
Generate a synthetic driving scenario with specified traffic and weather conditions using the ad-generative-models skill.
Dependency Matrix
Required Modules
None requiredComponents
scriptsreferencesassets
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: ad-generative-models Download link: https://github.com/RoboSafe-Lab/ad-safety-research-skills/archive/main.zip#ad-generative-models Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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