Multi-View Diffusion

Train a diffusion model to generate multiple consistent views of a 3D object from a single input image or text prompt, enabling 3D asset creation without explicit 3D supervision. Multi-view diffusion extends standard image diffusion to generate several images of the same object from different camera viewpoints, with cross-view consistency. The model conditions on a reference image and relative camera pose, and generates N views simultaneously using cross-attention between views. Training requires either multi-view renderings of 3D assets or video frames (where consecutive frames approximate multi-view). The generated views can then be fed into a 3D reconstruction method (NeRF, Gaussian Splatting) for full 3D asset creation.