OrthoPlanes: A Novel Representation for Better 3D-Awareness of GANs
Honglin He Zhuoqian Yang Shikai Li Bo Dai Wayne Wu
We present a new method for generating realistic and view-consistent images
with fine geometry from 2D image collections. Our method proposes a hybrid
explicit-implicit representation called \textbf{OrthoPlanes}, which encodes
fine-grained 3D information in feature maps that can be efficiently generated
by modifying 2D StyleGANs. Compared to previous representations, our method has
better scalability and expressiveness with clear and explicit information. As a
result, our method can handle more challenging view-angles and synthesize
articulated objects with high spatial degree of freedom. Experiments
demonstrate that our method achieves state-of-the-art results on FFHQ and SHHQ
datasets, both quantitatively and qualitatively. Project page:
\url{https://orthoplanes.github.io/}.