ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2310.05524
  4. Cited By
Parameterization-driven Neural Surface Reconstruction for
  Object-oriented Editing in Neural Rendering

Parameterization-driven Neural Surface Reconstruction for Object-oriented Editing in Neural Rendering

9 October 2023
Baixin Xu
Jiangbei Hu
Fei Hou
Kwan-Yee Lin
Wayne Wu
Chen Qian
Ying He
    3DH
ArXivPDFHTML

Papers citing "Parameterization-driven Neural Surface Reconstruction for Object-oriented Editing in Neural Rendering"

4 / 4 papers shown
Title
NeuMesh: Learning Disentangled Neural Mesh-based Implicit Field for
  Geometry and Texture Editing
NeuMesh: Learning Disentangled Neural Mesh-based Implicit Field for Geometry and Texture Editing
Bangbang Yang
Chong Bao
Junyi Zeng
Hujun Bao
Yinda Zhang
Zhaopeng Cui
Guofeng Zhang
3DH
AI4CE
184
155
0
25 Jul 2022
Neural Parameterization for Dynamic Human Head Editing
Neural Parameterization for Dynamic Human Head Editing
Li Ma
Xiaoyu Li
J. Liao
Xuan Wang
Qi Zhang
Jue Wang
Pedro Sander
3DH
125
19
0
01 Jul 2022
StylizedNeRF: Consistent 3D Scene Stylization as Stylized NeRF via 2D-3D
  Mutual Learning
StylizedNeRF: Consistent 3D Scene Stylization as Stylized NeRF via 2D-3D Mutual Learning
Yihua Huang
Yue He
Yu-Jie Yuan
Yu-Kun Lai
Lin Gao
164
148
0
24 May 2022
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
1