A Survey of Text-guided 3D Face Reconstruction
Mengyue Cen, Haoran Shen, Wangyan Zhao, Dingcheng Pan, Xiaoyi Feng · 2024
Text-guided 3D face reconstruction is an emerging field that leverages artificial intelligence to generate detailed and animatable 3D facial models from textual descriptions. This technology holds promise for revolutionizing digital content creation, avatar design, and virtual interaction by allowing users to convert textual imaginations into realistic 3D representations. This survey paper provides a comprehensive overview of the state-of-the-art methods in text-guided 3D face reconstruction, including ClipFace, DreamFace, TG-3DFace, and E3-FaceNet. We discuss their unique features, advantages, limitations, and the innovative techniques they employ to bridge the gap between natural language and 3D visual space. We also highlight the challenges that remain, such as achieving high fidelity and efficiency in the rendering process, and the potential for future advancements in this domain.