53 citations · 106 across the 24 of their papers we have counts for
4 papers · 1 filter
DS-MVSNet: Unsupervised Multi-view Stereo via Depth Synthesis
Jingliang Li, Zhengda Lu, Yiqun Wang +2
In recent years, supervised or unsupervised learning-based MVS methods achieved excellent performance compared with traditional methods. However, these methods only use the probabi…
EpiGRAF: Rethinking training of 3D GANs
Ivan Skorokhodov, Sergey Tulyakov, Yiqun Wang +1
A very recent trend in generative modeling is building 3D-aware generators from 2D image collections. To induce the 3D bias, such models typically rely on volumetric rendering, whi…
HF-NeuS: Improved Surface Reconstruction Using High-Frequency Details
Yiqun Wang, Ivan Skorokhodov, Peter Wonka
Neural rendering can be used to reconstruct implicit representations of shapes without 3D supervision. However, current neural surface reconstruction methods have difficulty learni…
DepthGAN: GAN-based Depth Generation of Indoor Scenes from Semantic Layouts
Yidi Li, Yiqun Wang, Zhengda Lu +1
Limited by the computational efficiency and accuracy, generating complex 3D scenes remains a challenging problem for existing generation networks. In this work, we propose DepthGAN…