Text to 3D Content Creation

Text-to-3D content creation aims to automatically generate three-dimensional models from textual descriptions, significantly reducing the time and expertise needed for 3D asset creation. Current research focuses on improving the fidelity, controllability, and efficiency of these models, often employing techniques like score distillation sampling, Gaussian splatting, and multi-view consistency checks within various neural network architectures. These advancements hold significant potential for diverse applications, including gaming, virtual reality, and robotics simulation, by automating a previously labor-intensive process.