Triplane Diffusion

Triplane diffusion is a rapidly developing technique leveraging the efficiency of 2D diffusion models to generate and manipulate 3D data. Research focuses on using triplane representations—three orthogonal planes encoding 3D information—as a proxy for complex 3D scenes, enabling faster training and inference compared to directly processing volumetric data. This approach is proving effective across diverse applications, including medical image reconstruction, 3D portrait video generation, and scene synthesis for autonomous driving, demonstrating significant improvements in speed and quality over existing methods. The resulting advancements are impacting various fields by enabling efficient and high-fidelity 3D content creation and manipulation.