3D Generator

3D generation research focuses on creating realistic three-dimensional models from various inputs, such as single images, text descriptions, or videos. Current efforts center on improving the speed, quality, and consistency of generated models, often employing Gaussian splatting, diffusion models, and implicit function representations. These advancements leverage techniques like geometric consistency priors and multi-view consistency to address limitations in existing methods, leading to more detailed and realistic 3D outputs. This field has significant implications for various applications, including computer graphics, virtual and augmented reality, and scientific visualization.