LOHO: Latent Optimization of Hairstyles via Orthogonalization

Rohit Saha; Brendan Duke; Florian Shkurti; Graham W. Taylor; Parham Aarabi

doi:10.1109/cvpr46437.2021.00202

CVPR2021顶会

LOHO: Latent Optimization of Hairstyles via Orthogonalization

Rohit Saha, Brendan Duke, Florian Shkurti, Graham W. Taylor, Parham Aarabi

DOI 出版方

2021年份

8顶会引用

摘要

Figure 1: Hairstyle transfer samples synthesized using LOHO. For given portrait images (a) and (d), LOHO is capable of manipulating hair attributes based on multiple input conditions. Inset images represent the target hair attributes in the order: appearance and style, structure, and shape. LOHO can transfer appearance and style (b), and perceptual structure (e) while keeping the background unchanged. Additionally, LOHO can change multiple hair attributes simultaneously and independently (c).