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Driving in the Matrix: Can Virtual Worlds Replace Human-Generated
  Annotations for Real World Tasks?

Driving in the Matrix: Can Virtual Worlds Replace Human-Generated Annotations for Real World Tasks?

6 October 2016
Matthew Johnson-Roberson
Charlie Barto
Rounak Mehta
S. N. Sridhar
Karl Rosaen
Ram Vasudevan
ArXivPDFHTML

Papers citing "Driving in the Matrix: Can Virtual Worlds Replace Human-Generated Annotations for Real World Tasks?"

17 / 17 papers shown
Title
RT-DATR:Real-time Unsupervised Domain Adaptive Detection Transformer with Adversarial Feature Learning
RT-DATR:Real-time Unsupervised Domain Adaptive Detection Transformer with Adversarial Feature Learning
Feng Lv
Chunlong Xia
Shuo Wang
Huo Cao
ViT
134
0
0
12 Apr 2025
Scaling Text-Rich Image Understanding via Code-Guided Synthetic Multimodal Data Generation
Scaling Text-Rich Image Understanding via Code-Guided Synthetic Multimodal Data Generation
Yue Yang
Ajay Patel
Matt Deitke
Tanmay Gupta
Luca Weihs
...
Mark Yatskar
Chris Callison-Burch
Ranjay Krishna
Aniruddha Kembhavi
Christopher Clark
SyDa
148
2
0
20 Feb 2025
The Unmet Promise of Synthetic Training Images: Using Retrieved Real Images Performs Better
The Unmet Promise of Synthetic Training Images: Using Retrieved Real Images Performs Better
Scott Geng
Cheng-Yu Hsieh
Vivek Ramanujan
Matthew Wallingford
Chun-Liang Li
Pang Wei Koh
Ranjay Krishna
DiffM
104
7
0
03 Jan 2025
Paint Outside the Box: Synthesizing and Selecting Training Data for Visual Grounding
Paint Outside the Box: Synthesizing and Selecting Training Data for Visual Grounding
Zilin Du
Haoxin Li
Jianfei Yu
Boyang Li
389
0
0
01 Dec 2024
Can Medical Vision-Language Pre-training Succeed with Purely Synthetic Data?
Can Medical Vision-Language Pre-training Succeed with Purely Synthetic Data?
Che Liu
Zhongwei Wan
Haozhe Wang
Yinda Chen
T. Qaiser
Chen Jin
Fariba Yousefi
Nikolay Burlutskiy
Rossella Arcucci
VLM
SyDa
LM&MA
MedIm
101
2
0
17 Oct 2024
All for One, and One for All: UrbanSyn Dataset, the third Musketeer of Synthetic Driving Scenes
All for One, and One for All: UrbanSyn Dataset, the third Musketeer of Synthetic Driving Scenes
J. L. Gómez
Manuel Silva
Antonio Seoane
Agnes Borrás
Mario Noriega
Germán Ros
Jose A. Iglesias-Guitian
Antonio M. López
3DPC
164
12
0
19 Dec 2023
Adapting Object Detectors with Conditional Domain Normalization
Adapting Object Detectors with Conditional Domain Normalization
Peng Su
Kun Wang
Xingyu Zeng
Shixiang Tang
Dapeng Chen
Di Qiu
Xiaogang Wang
144
85
0
16 Mar 2020
Unbiased Mean Teacher for Cross-domain Object Detection
Unbiased Mean Teacher for Cross-domain Object Detection
Jinhong Deng
Wen Li
Yuhua Chen
Lixin Duan
165
292
0
02 Mar 2020
Scene recognition with CNNs: objects, scales and dataset bias
Scene recognition with CNNs: objects, scales and dataset bias
Luis Herranz
Shuqiang Jiang
Xiangyang Li
52
213
0
21 Jan 2018
Safe Trajectory Synthesis for Autonomous Driving in Unforeseen
  Environments
Safe Trajectory Synthesis for Autonomous Driving in Unforeseen Environments
Shreyas Kousik
S. Vaskov
Matthew Johnson-Roberson
Ram Vasudevan
58
56
0
28 Apr 2017
Playing for Data: Ground Truth from Computer Games
Playing for Data: Ground Truth from Computer Games
Stephan R. Richter
Vibhav Vineet
Stefan Roth
V. Koltun
VLM
118
2,002
0
07 Aug 2016
The Cityscapes Dataset for Semantic Urban Scene Understanding
The Cityscapes Dataset for Semantic Urban Scene Understanding
Marius Cordts
Mohamed Omran
Sebastian Ramos
Timo Rehfeld
Markus Enzweiler
Rodrigo Benenson
Uwe Franke
Stefan Roth
Bernt Schiele
826
11,540
0
06 Apr 2016
MXNet: A Flexible and Efficient Machine Learning Library for
  Heterogeneous Distributed Systems
MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems
Tianqi Chen
Mu Li
Yutian Li
Min Lin
Naiyan Wang
Minjie Wang
Tianjun Xiao
Bing Xu
Chiyuan Zhang
Zheng Zhang
160
2,243
0
03 Dec 2015
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal
  Networks
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Shaoqing Ren
Kaiming He
Ross B. Girshick
Jian Sun
AIMat
ObjD
432
61,900
0
04 Jun 2015
Render for CNN: Viewpoint Estimation in Images Using CNNs Trained with
  Rendered 3D Model Views
Render for CNN: Viewpoint Estimation in Images Using CNNs Trained with Rendered 3D Model Views
Hao Su
C. Qi
Yangyan Li
Leonidas Guibas
97
737
0
21 May 2015
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAtt
MDE
1.2K
99,991
0
04 Sep 2014
ImageNet Large Scale Visual Recognition Challenge
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky
Jia Deng
Hao Su
J. Krause
S. Satheesh
...
A. Karpathy
A. Khosla
Michael S. Bernstein
Alexander C. Berg
Li Fei-Fei
VLM
ObjD
1.3K
39,383
0
01 Sep 2014
1