OpenDriveLab/Nexus
[ICCV 2025] Nexus: Decoupled Diffusion Sparks Adaptive Scene Generation
This project helps automotive engineers and autonomous driving system designers create and test realistic driving scenarios. It takes real-world map data and vehicle interaction patterns, then generates diverse, safety-critical driving scenes, including hazardous behaviors. The output is a controllable simulation of complex driving situations for testing autonomous vehicle performance.
109 stars.
Use this if you need to generate adaptable, goal-directed driving scenarios, especially safety-critical ones, for autonomous vehicle development and testing.
Not ideal if you are looking for a general-purpose image generation tool or if your primary focus is not on detailed, controllable driving scene simulation.
Stars
109
Forks
10
Language
Python
License
Apache-2.0
Category
Last pushed
Jan 06, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/OpenDriveLab/Nexus"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
UCSC-VLAA/story-iter
[ICLR 2026] A Training-free Iterative Framework for Long Story Visualization
PaddlePaddle/PaddleMIX
Paddle Multimodal Integration and eXploration, supporting mainstream multi-modal tasks,...
keivalya/mini-vla
a minimal, beginner-friendly VLA to show how robot policies can fuse images, text, and states to...
adobe-research/custom-diffusion
Custom Diffusion: Multi-Concept Customization of Text-to-Image Diffusion (CVPR 2023)
byliutao/1Prompt1Story
🔥ICLR 2025 (Spotlight) One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation...