1st Place Solution for ICCV 2023 OmniObject3D Challenge: Sparse-View
  Reconstruction
Hang Du Yaping Xue Weidong Dai Xuejun Yan Jingjing Wang
In this report, we present the 1st place solution for ICCV 2023 OmniObject3D
Challenge: Sparse-View Reconstruction. The challenge aims to evaluate
approaches for novel view synthesis and surface reconstruction using only a few
posed images of each object. We utilize Pixel-NeRF as the basic model, and
apply depth supervision as well as coarse-to-fine positional encoding. The
experiments demonstrate the effectiveness of our approach in improving
sparse-view reconstruction quality. We ranked first in the final test with a
PSNR of 25.44614.