Search Results for author:
Found 3 papers, 3 papers with code
Relaxing Accurate Initialization Constraint for 3D Gaussian Splatting
Through extensive analysis of SfM initialization in the frequency domain and analysis of a 1D regression task with multiple 1D Gaussians, we propose a novel optimization strategy dubbed RAIN-GS (Relaxing Accurate Initialization Constraint for 3D Gaussian Splatting), that successfully trains 3D Gaussians from random point clouds.
DaRF: Boosting Radiance Fields from Sparse Inputs with Monocular Depth Adaptation
Employing monocular depth estimation (MDE) networks, pretrained on large-scale RGB-D datasets, with powerful generalization capability would be a key to solving this problem: however, using MDE in conjunction with NeRF comes with a new set of challenges due to various ambiguity problems exhibited by monocular depths.
MaskingDepth: Masked Consistency Regularization for Semi-supervised Monocular Depth Estimation
We propose MaskingDepth, a novel semi-supervised learning framework for monocular depth estimation to mitigate the reliance on large ground-truth depth quantities.
