Convolutional Neural Networks on non-uniform geometrical signals using
Euclidean spectral transformation

Convolutional Neural Networks on non-uniform geometrical signals using Euclidean spectral transformation

7 January 2019

Matthias Nießner

Papers citing "Convolutional Neural Networks on non-uniform geometrical signals using Euclidean spectral transformation"

7 / 7 papers shown

Title
Poly2Vec: Polymorphic Fourier-Based Encoding of Geospatial Objects for GeoAI Applications Maria Despoina Siampou Jialiang Li John Krumm Cyrus Shahabi Hua Lu 27 1 0 27 Aug 2024
Towards General-Purpose Representation Learning of Polygonal Geometries Gengchen Mai C. Jiang Weiwei Sun Rui Zhu Yao Xuan Ling Cai K. Janowicz Stefano Ermon Ni Lao 35 38 0 29 Sep 2022
Local Implicit Grid Representations for 3D Scenes C. Jiang Avneesh Sud A. Makadia Jingwei Huang Matthias Nießner Thomas Funkhouser 3DPC 240 558 0 19 Mar 2020
DDSL: Deep Differentiable Simplex Layer for Learning Geometric Signals C. Jiang Dana Lynn Ona Lansigan P. Marcus Matthias Nießner 11 11 0 30 Jan 2019
6-DoF Object Pose from Semantic Keypoints Georgios Pavlakos Xiaowei Zhou Aaron Chan Konstantinos G. Derpanis Kostas Daniilidis 105 392 0 14 Mar 2017
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 263 1,812 0 25 Nov 2016
Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling Jiajun Wu Chengkai Zhang Tianfan Xue Bill Freeman J. Tenenbaum GAN 191 1,942 0 24 Oct 2016