Neural Fields as Learnable Kernels for 3D Reconstruction

Neural Fields as Learnable Kernels for 3D Reconstruction

26 November 2021

Francis Williams

Joan Bruna

Sanja Fidler

Papers citing "Neural Fields as Learnable Kernels for 3D Reconstruction"

11 / 11 papers shown

Title
Point2Quad: Generating Quad Meshes from Point Clouds via Face Prediction Zezeng Li Zhihui Qi Weimin Wang Ziliang Wang Junyi Duan Na Lei 3DPC 53 0 0 28 Apr 2025
Oriented-grid Encoder for 3D Implicit Representations Arihant Gaur Goncalo Dias Pais Pedro Miraldo 22 0 0 09 Feb 2024
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 57 0 05 May 2022
Vector Neurons: A General Framework for SO(3)-Equivariant Networks Congyue Deng Or Litany Yueqi Duan A. Poulenard Andrea Tagliasacchi Leonidas J. Guibas 3DPC 102 314 0 25 Apr 2021
Diffusion Probabilistic Models for 3D Point Cloud Generation Shitong Luo Wei Hu 3DPC 167 711 0 02 Mar 2021
SDF-SRN: Learning Signed Distance 3D Object Reconstruction from Static Images Chen-Hsuan Lin Chaoyang Wang Simon Lucey 73 97 0 20 Oct 2020
Local Implicit Grid Representations for 3D Scenes C. Jiang Avneesh Sud A. Makadia Jingwei Huang Matthias Nießner Thomas Funkhouser 3DPC 214 556 0 19 Mar 2020
Convolutional Occupancy Networks Songyou Peng Michael Niemeyer L. Mescheder Marc Pollefeys Andreas Geiger 3DV AI4CE 212 968 0 10 Mar 2020
Deep Mesh Reconstruction from Single RGB Images via Topology Modification Networks J. Pan Xiaoguang Han Weikai Chen Jiapeng Tang K. Jia 96 187 0 01 Sep 2019
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation C. Qi Hao Su Kaichun Mo Leonidas J. Guibas 3DH 3DPC 3DV PINN 219 13,886 0 02 Dec 2016