Neural Splines: Fitting 3D Surfaces with Infinitely-Wide Neural Networks

Neural Splines: Fitting 3D Surfaces with Infinitely-Wide Neural Networks

24 June 2020

Francis Williams

Matthew Trager

Joan Bruna

Papers citing "Neural Splines: Fitting 3D Surfaces with Infinitely-Wide Neural Networks"

9 / 9 papers shown

Title
Few-shot point cloud reconstruction and denoising via learned Guassian splats renderings and fine-tuned diffusion features Pietro Bonazzi Marie-Julie Rakatosaona Marco Cannici Federico Tombari Davide Scaramuzza 16 0 0 01 Apr 2024
Mixing-Denoising Generalizable Occupancy Networks Amine Ouasfi A. Boukhayma 3DPC AI4CE 3DV 16 8 0 20 Nov 2023
Unsupervised Inference of Signed Distance Functions from Single Sparse Point Clouds without Learning Priors Chao Chen Yu-Shen Liu Zhizhong Han 3DPC 22 28 0 25 Mar 2023
A Review of Deep Learning-Powered Mesh Reconstruction Methods Zhiqin Chen 3DV 35 2 0 06 Mar 2023
Surface Reconstruction from Point Clouds: A Survey and a Benchmark Zhangjin Huang Yuxin Wen Zihao Wang Jinjuan Ren K. Jia 3DV 3DPC 19 60 0 05 May 2022
POCO: Point Convolution for Surface Reconstruction Alexandre Boulch Renaud Marlet 3DPC 3DV 22 125 0 05 Jan 2022
Neural Fields as Learnable Kernels for 3D Reconstruction Francis Williams Zan Gojcic S. Khamis Denis Zorin Joan Bruna Sanja Fidler Or Litany 42 66 0 26 Nov 2021
Neural Fields in Visual Computing and Beyond Yiheng Xie Towaki Takikawa Shunsuke Saito Or Litany Shiqin Yan Numair Khan Federico Tombari James Tompkin Vincent Sitzmann Srinath Sridhar 3DH 19 613 0 22 Nov 2021
Phase Transitions, Distance Functions, and Implicit Neural Representations Y. Lipman AI4CE 11 38 0 14 Jun 2021