3D Generation

3D generation research focuses on creating realistic three-dimensional models from various inputs like text, images, or existing 3D models. Current efforts center on improving the quality, efficiency, and controllability of generation, employing techniques such as diffusion models, autoregressive transformers, and neural radiance fields, often within a multi-view framework. These advancements are significant for fields like computer graphics, virtual reality, and product design, enabling faster and more intuitive creation of high-fidelity 3D assets. The development of efficient and robust methods for handling diverse data types and achieving high-resolution, consistent outputs remains a key focus.