DELIFFAS: Deformable Light Fields for Fast Avatar Synthesis

Title: DELIFFAS: Deformable Light Fields for Fast Avatar Synthesis Author List (Semicolon Separated): Youngjoong Kwon, Lingjie Liu, Henry Fuchs, Marc Habermann, Christian Theobalt Venue: Extra: https://vcai.mpi-inf.mpg.de/projects/DELIFFAS/ Date: Abstract:

Generating controllable and photorealistic digital human avatars is a long-standing
and important problem in Vision and Graphics. Recent methods have shown great
progress in terms of either photorealism or inference speed while the combination
of the two desired properties still remains unsolved. To this end, we propose
a novel method, called DELIFFAS, which parameterizes the appearance of the
human as a surface light field that is attached to a controllable and deforming
human mesh model. At the core, we represent the light field around the human
with a deformable two-surface parameterization, which enables fast and accurate
inference of the human appearance. This allows perceptual supervision on the
full image compared to previous approaches that could only supervise individual
pixels or small patches due to their slow runtime. Our carefully designed human
representation and supervision strategy leads to state-of-the-art synthesis results
and inference time. The video results and code are available at https://vcai.
mpi-inf.mpg.de/projects/DELIFFAS

Paper (Internally Stored): Paper (Externally Stored): https://arxiv.org/pdf/2310.11449.pdf Video (Externally Stored): Video (Streaming): BibTeX: DOI: http://arxiv.org/abs/2310.11449