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Taylor3DNet: Fast 3D Shape Inference With Landmark Points Based Taylor
  Series

Taylor3DNet: Fast 3D Shape Inference With Landmark Points Based Taylor Series

18 January 2022
Yuting Xiao
Jiale Xu
Shenghua Gao
    3DV
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Papers citing "Taylor3DNet: Fast 3D Shape Inference With Landmark Points Based Taylor Series"

5 / 5 papers shown
Title
Local Implicit Grid Representations for 3D Scenes
Local Implicit Grid Representations for 3D Scenes
C. Jiang
Avneesh Sud
A. Makadia
Jingwei Huang
Matthias Nießner
Thomas Funkhouser
3DPC
225
558
0
19 Mar 2020
Curriculum DeepSDF
Curriculum DeepSDF
Yueqi Duan
Haidong Zhu
He-Nan Wang
L. Yi
Ram Nevatia
Leonidas J. Guibas
65
94
0
19 Mar 2020
Convolutional Occupancy Networks
Convolutional Occupancy Networks
Songyou Peng
Michael Niemeyer
L. Mescheder
Marc Pollefeys
Andreas Geiger
3DV
AI4CE
223
971
0
10 Mar 2020
PointNet: Deep Learning on Point Sets for 3D Classification and
  Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
C. Qi
Hao Su
Kaichun Mo
Leonidas J. Guibas
3DH
3DPC
3DV
PINN
222
14,099
0
02 Dec 2016
Learning a Probabilistic Latent Space of Object Shapes via 3D
  Generative-Adversarial Modeling
Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling
Jiajun Wu
Chengkai Zhang
Tianfan Xue
Bill Freeman
J. Tenenbaum
GAN
168
1,940
0
24 Oct 2016
1