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. 2411.06166
  4. Cited By
Towards an Efficient Synthetic Image Data Pipeline for Training
  Vision-Based Robot Systems

Towards an Efficient Synthetic Image Data Pipeline for Training Vision-Based Robot Systems

9 November 2024
Peter Gavriel
Adam Norton
Kenneth Kimble
Megan Zimmerman
ArXiv (abs)PDFHTML

Papers citing "Towards an Efficient Synthetic Image Data Pipeline for Training Vision-Based Robot Systems"

11 / 11 papers shown
Title
A Survey on 3D Gaussian Splatting
A Survey on 3D Gaussian Splatting
Guikun Chen
Wenguan Wang
3DGS
178
191
0
08 Jan 2024
NeuSG: Neural Implicit Surface Reconstruction with 3D Gaussian Splatting Guidance
NeuSG: Neural Implicit Surface Reconstruction with 3D Gaussian Splatting Guidance
Hanlin Chen
Chen Li
Gim Hee Lee
Gim Hee Lee
3DGS
120
83
0
01 Dec 2023
SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh
  Reconstruction and High-Quality Mesh Rendering
SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh Reconstruction and High-Quality Mesh Rendering
Antoine Guédon
Vincent Lepetit
3DGS
50
367
0
21 Nov 2023
Photo-realistic Neural Domain Randomization
Photo-realistic Neural Domain Randomization
Sergey Zakharov
Rares Andrei Ambrus
Vitor Campagnolo Guizilini
Wadim Kehl
Adrien Gaidon
100
10
0
23 Oct 2022
Kubric: A scalable dataset generator
Kubric: A scalable dataset generator
Klaus Greff
Francois Belletti
Lucas Beyer
Carl Doersch
Yilun Du
...
Ziyu Wang
Tianhao Wu
K. M. Yi
Fangcheng Zhong
Andrea Tagliasacchi
105
267
0
07 Mar 2022
ParaPose: Parameter and Domain Randomization Optimization for Pose
  Estimation using Synthetic Data
ParaPose: Parameter and Domain Randomization Optimization for Pose Estimation using Synthetic Data
Frederik Hagelskjær
A. Buch
OOD
64
8
0
02 Mar 2022
Unity Perception: Generate Synthetic Data for Computer Vision
Unity Perception: Generate Synthetic Data for Computer Vision
S. Borkman
A. Crespi
S. Dhakad
Sujoy Ganguly
Jonathan Hogins
...
Cesar Romero
Wesley Smith
Alex Thaman
Samuel Warren
Nupur Yadav
3DVSyDaVLM
61
101
0
09 Jul 2021
BlenderProc
BlenderProc
Maximilian Denninger
Martin Sundermeyer
Dominik Winkelbauer
Youssef Zidan
Dmitry Olefir
Mohamad Elbadrawy
Ahsan Lodhi
Harinandan Katam
3DHSSeg
67
144
0
25 Oct 2019
Training Deep Networks with Synthetic Data: Bridging the Reality Gap by
  Domain Randomization
Training Deep Networks with Synthetic Data: Bridging the Reality Gap by Domain Randomization
Jonathan Tremblay
Aayush Prakash
David Acuna
M. Brophy
Varun Jampani
Cem Anil
Thang To
Eric Cameracci
Shaad Boochoon
Stan Birchfield
OOD
78
818
0
18 Apr 2018
Deep Visual Domain Adaptation: A Survey
Deep Visual Domain Adaptation: A Survey
Mei Wang
Weihong Deng
OOD
79
2,014
0
10 Feb 2018
A Survey of Structure from Motion
A Survey of Structure from Motion
Onur Özyesil
V. Voroninski
Ronen Basri
A. Singer
80
389
0
30 Jan 2017
1