4 citations · 4 across the 1 of their papers we have counts for
5 papers
Iso-Points: Optimizing Neural Implicit Surfaces with Hybrid Representations
Wang Yifan, Shihao Wu, Cengiz Oztireli +1
Neural implicit functions have emerged as a powerful representation for surfaces in 3D. Such a function can encode a high quality surface with intricate details into the parameters…
Neural Cages for Detail-Preserving 3D Deformations
Wang Yifan, Noam Aigerman, Vladimir G. Kim +2
We propose a novel learnable representation for detail-preserving shape deformation. The goal of our method is to warp a source shape to match the general structure of a target sha…
Differentiable Surface Splatting for Point-based Geometry Processing
Wang Yifan, Felice Serena, Shihao Wu +2
We propose Differentiable Surface Splatting (DSS), a high-fidelity differentiable renderer for point clouds. Gradients for point locations and normals are carefully designed to han…
Patch-based Progressive 3D Point Set Upsampling
Wang Yifan, Shihao Wu, Hui Huang +2
We present a detail-driven deep neural network for point set upsampling. A high-resolution point set is essential for point-based rendering and surface reconstruction. Inspired by…
A Fully Progressive Approach to Single-Image Super-Resolution
Yifan Wang, Federico Perazzi, Brian McWilliams +3
Recent deep learning approaches to single image super-resolution have achieved impressive results in terms of traditional error measures and perceptual quality. However, in each ca…