Search Results for author:
Found 8 papers, 4 papers with code
Neural-ABC: Neural Parametric Models for Articulated Body with Clothes
In this paper, we introduce Neural-ABC, a novel parametric model based on neural implicit functions that can represent clothed human bodies with disentangled latent spaces for identity, clothing, shape, and pose.
DynoSurf: Neural Deformation-based Temporally Consistent Dynamic Surface Reconstruction
Furthermore, we propose a learnable deformation representation based on the learnable control points and blending weights, which can deform the template surface non-rigidly while maintaining the consistency of the local shape.
Fast and Robust Non-Rigid Registration Using Accelerated Majorization-Minimization
In this paper, we propose a formulation for robust non-rigid registration based on a globally smooth robust norm for alignment and regularization, which can effectively handle outliers and partial overlaps.
A Survey of Non-Rigid 3D Registration
Non-rigid registration computes an alignment between a source surface with a target surface in a non-rigid manner.
A Robust Loss for Point Cloud Registration
The performance of surface registration relies heavily on the metric used for the alignment error between the source and target shapes.
Fast and Robust Iterative Closest Point
On challenging datasets with noises and partial overlaps, we achieve similar or better accuracy than Sparse ICP while being at least an order of magnitude faster.
Quasi-Newton Solver for Robust Non-Rigid Registration
Imperfect data (noise, outliers and partial overlap) and high degrees of freedom make non-rigid registration a classical challenging problem in computer vision.
Fast K-Means Clustering with Anderson Acceleration
We propose a novel method to accelerate Lloyd's algorithm for K-Means clustering.
