arXiv:2303.02688

Text2Face: A Multi-Modal 3D Face Model

Will Rowan, Patrik Huber, Nick Pears, Andrew Keeling

제출 2023-03-05

원문 초록

We present the first 3D morphable modelling approach, whereby 3D face shape can be directly and completely defined using a textual prompt. Building on work in multi-modal learning, we extend the FLAME head model to a common image-and-text latent space. This allows for direct 3D Morphable Model (3DMM) parameter generation and therefore shape manipulation from textual descriptions. Our method, Text2Face, has many applications; for example: generating police photofits where the input is already in natural language. It further enables multi-modal 3DMM image fitting to sketches and sculptures, as well as images.

함께 살펴볼 논문

공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.

arXiv:2507.10539공통 태그 model공식 코드 · Papers with Code

Graph World Model

토론

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