Image to 3D

Image-to-3D generation aims to create realistic three-dimensional models from single or multiple two-dimensional images, focusing on improving both the speed and quality of 3D asset creation. Current research emphasizes using diffusion models, often combined with techniques like Gaussian splatting or neural radiance fields (NeRFs), to generate multi-view consistent images and high-resolution meshes. These advancements are significant for various applications, including virtual and augmented reality, computer-aided design, and digital content creation, by offering faster and more efficient methods for generating high-fidelity 3D models.