Research Paper#Computer Vision, Autonomous Driving, 3D Scene Generation🔬 ResearchAnalyzed: Jan 3, 2026 19:43
SCPainter: Realistic 3D Asset Insertion and Novel View Synthesis for Autonomous Driving
Published:Dec 27, 2025 21:28
•1 min read
•ArXiv
Analysis
This paper addresses a critical challenge in autonomous driving simulation: generating diverse and realistic training data. By unifying 3D asset insertion and novel view synthesis, SCPainter aims to improve the robustness and safety of autonomous driving models. The integration of 3D Gaussian Splat assets and diffusion-based generation is a novel approach to achieve realistic scene integration, particularly focusing on lighting and shadow realism, which is crucial for accurate simulation. The use of the Waymo Open Dataset for evaluation provides a strong benchmark.
Key Takeaways
- •Proposes a unified framework (SCPainter) for realistic 3D asset insertion and novel view synthesis.
- •Integrates 3D Gaussian Splat assets and diffusion-based generation for realistic scene integration.
- •Addresses the challenge of creating diverse and realistic training data for autonomous driving.
- •Evaluated on the Waymo Open Dataset, demonstrating its capability.
Reference
“SCPainter integrates 3D Gaussian Splat (GS) car asset representations and 3D scene point clouds with diffusion-based generation to jointly enable realistic 3D asset insertion and NVS.”