ad-generative-models
ad-generative-models is a Computer vision skill for AI agents, published by RoboSafe-Lab in the ad-safety-research-skills repository on GitHub. Skillspace rates ad-generative-models D (62/100) and it passed the safety scan; the rating is based on static analysis only.
Generative models for autonomous driving: world models (GAIA-1, DriveDreamer, GenAD, UniSim), diffusion models (CTG++, DiffScene, MagicDrive), flow matching, and 3D Gaussian Splatting (StreetGaussians, DrivingGaussian) for scene generation, sensor data synthesis, scenario augmentation, and closed-loop simulation. Use when researching or implementing generative approaches for AD data, simulation, or planning.
- Grade
- D
- Quality
- 62 / 100
- Safety
- Passed
- GitHub stars
- 26
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 96 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- Low-risk patterns
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- mentions secrets in text
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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