  3D textured face reconstruction from sketches applicable in many scenarios
such as animation, 3D avatars, artistic design, missing people search, etc., is
a highly promising but underdeveloped research topic. On the one hand, the
stylistic diversity of sketches leads to existing sketch-to-3D-face methods
only being able to handle pose-limited and realistically shaded sketches. On
the other hand, texture plays a vital role in representing facial appearance,
yet sketches lack this information, necessitating additional texture control in
the reconstruction process. This paper proposes a novel method for
reconstructing controllable textured and detailed 3D faces from sketches, named
S2TD-Face. S2TD-Face introduces a two-stage geometry reconstruction framework
that directly reconstructs detailed geometry from the input sketch. To keep
geometry consistent with the delicate strokes of the sketch, we propose a novel
sketch-to-geometry loss that ensures the reconstruction accurately fits the
input features like dimples and wrinkles. Our training strategies do not rely
on hard-to-obtain 3D face scanning data or labor-intensive hand-drawn sketches.
Furthermore, S2TD-Face introduces a texture control module utilizing text
prompts to select the most suitable textures from a library and seamlessly
integrate them into the geometry, resulting in a 3D detailed face with
controllable texture. S2TD-Face surpasses existing state-of-the-art methods in
extensive quantitative and qualitative experiments. Our project is available at
https://github.com/wang-zidu/S2TD-Face .
