Search Results for author:
Found 5 papers, 2 papers with code
Generalizable 3D Scene Reconstruction via Divide and Conquer from a Single View
We therefore propose a hybrid method following a divide-and-conquer strategy.
RANRAC: Robust Neural Scene Representations via Random Ray Consensus
We demonstrate the compatibility and potential of our solution for both photo-realistic robust multi-view reconstruction from real-world images based on neural radiance fields and for single-shot reconstruction based on light-field networks.
Neural Haircut: Prior-Guided Strand-Based Hair Reconstruction
The second stage then estimates a strand-level hair reconstruction by reconciling in a single optimization process the coarse volumetric constraints with hair strand and hairstyle priors learned from the synthetic data.
Sphere-Guided Training of Neural Implicit Surfaces
In recent years, neural distance functions trained via volumetric ray marching have been widely adopted for multi-view 3D reconstruction.
