Adobe’s DMV3D Achieves SOTA Performance for High-Fidelity 3D Objects Generation Within Seconds

A research team innovative single-stage category-agnostic diffusion model. This model can generate 3D Neural Radiance Fields (NeRFs) from either text or a single-image input condition through direct model inference, enabling the creation of diverse high-fidelity 3D objects in just 30s/asset.

3d objects 3d reconstruction adobe ai artificial intelligence deep-neural-networks diffusion diffusion model diverse enabling fidelity fields generate image inference machine learning machine learning & data science ml neural radiance fields objects performance research research team sota stage team technology text through