Adobe’s DMV3D Achieves SOTA Performance for High-Fidelity 3D Objects Generation Within Seconds | Synced
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 direc...
Source: Synced | AI Technology & Industry Review
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.