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Representing 3D Shapes with Probabilistic Directed Distance Fields

Representing 3D Shapes with Probabilistic Directed Distance Fields

10 December 2021
Tristan Aumentado-Armstrong
Stavros Tsogkas
Sven J. Dickinson
Allan D. Jepson
ArXivPDFHTML

Papers citing "Representing 3D Shapes with Probabilistic Directed Distance Fields"

5 / 5 papers shown
Title
Reconstructive Latent-Space Neural Radiance Fields for Efficient 3D
  Scene Representations
Reconstructive Latent-Space Neural Radiance Fields for Efficient 3D Scene Representations
Tristan Aumentado-Armstrong
Ashkan Mirzaei
Marcus A. Brubaker
J. Kelly
Alex Levinshtein
Konstantinos G. Derpanis
Igor Gilitschenski
22
4
0
27 Oct 2023
FIRe: Fast Inverse Rendering using Directional and Signed Distance
  Functions
FIRe: Fast Inverse Rendering using Directional and Signed Distance Functions
Tarun Yenamandra
A. Tewari
Nan Yang
Florian Bernard
Christian Theobalt
Daniel Cremers
11
7
0
30 Mar 2022
SDF-SRN: Learning Signed Distance 3D Object Reconstruction from Static
  Images
SDF-SRN: Learning Signed Distance 3D Object Reconstruction from Static Images
Chen-Hsuan Lin
Chaoyang Wang
Simon Lucey
73
99
0
20 Oct 2020
Shape and Viewpoint without Keypoints
Shape and Viewpoint without Keypoints
Shubham Goel
Angjoo Kanazawa
Jitendra Malik
3DV
89
108
0
21 Jul 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
14,087
0
02 Dec 2016
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