Text to 4D

Text-to-4D generation aims to create dynamic 3D scenes from textual descriptions, representing a significant advancement in computer graphics and AI. Current research focuses on improving the realism and consistency of generated 4D content by employing techniques like mesh-based animation, hybrid priors from text-to-video models, and pixel-level alignments with target videos, often utilizing Gaussian splatting or neural radiance fields for representation. These advancements are driving progress in fields like animation, simulation, and digital content creation, offering more efficient and intuitive methods for generating high-fidelity dynamic 3D models.