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How much real data do we actually need: Analyzing object detection
  performance using synthetic and real data

How much real data do we actually need: Analyzing object detection performance using synthetic and real data

16 July 2019
F. Nowruzi
Prince Kapoor
Dhanvin Kolhatkar
Fahed Al Hassanat
R. Laganière
Julien Rebut
ArXivPDFHTML

Papers citing "How much real data do we actually need: Analyzing object detection performance using synthetic and real data"

14 / 14 papers shown
Title
Is AI currently capable of identifying wild oysters? A comparison of human annotators against the AI model, ODYSSEE
Is AI currently capable of identifying wild oysters? A comparison of human annotators against the AI model, ODYSSEE
Brendan Campbell
Alan Williams
Kleio Baxevani
Alyssa Campbell
Rushabh Dhoke
...
Arjun Suresh
Alhim Vera
Arthur Trembanis
Herbert G. Tanner
Edward Hale
57
0
0
06 May 2025
Efficacy of Synthetic Data as a Benchmark
Efficacy of Synthetic Data as a Benchmark
Gaurav Maheshwari
Dmitry Ivanov
Kevin El Haddad
SyDa
18
6
0
18 Sep 2024
Advancing Fine-Grained Classification by Structure and Subject Preserving Augmentation
Advancing Fine-Grained Classification by Structure and Subject Preserving Augmentation
Eyal Michaeli
Ohad Fried
57
1
0
20 Jun 2024
Synthetic Data Generation for Bridging Sim2Real Gap in a Production
  Environment
Synthetic Data Generation for Bridging Sim2Real Gap in a Production Environment
Parth Rawal
Mrunal Sompura
Wolfgang Hintze
23
0
0
18 Nov 2023
Radar-Camera Fusion for Object Detection and Semantic Segmentation in
  Autonomous Driving: A Comprehensive Review
Radar-Camera Fusion for Object Detection and Semantic Segmentation in Autonomous Driving: A Comprehensive Review
Shanliang Yao
Runwei Guan
Xiaoyu Huang
Zhuoxiao Li
Xiangyu Sha
...
Eng Gee Lim
H. Seo
Ka Lok Man
Xiaohui Zhu
Yutao Yue
34
91
0
20 Apr 2023
Quantifying the LiDAR Sim-to-Real Domain Shift: A Detailed Investigation
  Using Object Detectors and Analyzing Point Clouds at Target-Level
Quantifying the LiDAR Sim-to-Real Domain Shift: A Detailed Investigation Using Object Detectors and Analyzing Point Clouds at Target-Level
Sebastian Huch
Luca Scalerandi
Esteban Rivera
Markus Lienkamp
3DPC
21
16
0
03 Mar 2023
How many radiographs are needed to re-train a deep learning system for
  object detection?
How many radiographs are needed to re-train a deep learning system for object detection?
Raniere Silva
Khizar Hayat
Christopher Riggs
M. Doube
MedIm
16
0
0
17 Oct 2022
TRoVE: Transforming Road Scene Datasets into Photorealistic Virtual
  Environments
TRoVE: Transforming Road Scene Datasets into Photorealistic Virtual Environments
Shubham Dokania
A. Subramanian
Manmohan Chandraker
C. V. Jawahar
24
6
0
16 Aug 2022
Sim2Air - Synthetic aerial dataset for UAV monitoring
Sim2Air - Synthetic aerial dataset for UAV monitoring
A. Barišić
Frano Petrić
Stjepan Bogdan
29
21
0
11 Oct 2021
VersatileGait: A Large-Scale Synthetic Gait Dataset with
  Fine-GrainedAttributes and Complicated Scenarios
VersatileGait: A Large-Scale Synthetic Gait Dataset with Fine-GrainedAttributes and Complicated Scenarios
Huanzhang Dou
Wenhu Zhang
Pengyi Zhang
Yuhan Zhao
Songyuan Li
Zequn Qin
Fei Wu
Lin Dong
Xi Li
SLR
45
16
0
05 Jan 2021
SVIRO: Synthetic Vehicle Interior Rear Seat Occupancy Dataset and
  Benchmark
SVIRO: Synthetic Vehicle Interior Rear Seat Occupancy Dataset and Benchmark
S. Cruz
Oliver Wasenmüller
H. Beise
Thomas Stifter
D. Stricker
17
43
0
10 Jan 2020
Synthetic Data for Deep Learning
Synthetic Data for Deep Learning
Sergey I. Nikolenko
44
348
0
25 Sep 2019
Fully Convolutional Adaptation Networks for Semantic Segmentation
Fully Convolutional Adaptation Networks for Semantic Segmentation
Yiheng Zhang
Zhaofan Qiu
Ting Yao
Dong Liu
Tao Mei
SSeg
OOD
158
349
0
23 Apr 2018
ENet: A Deep Neural Network Architecture for Real-Time Semantic
  Segmentation
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
Adam Paszke
Abhishek Chaurasia
Sangpil Kim
Eugenio Culurciello
SSeg
216
2,056
0
07 Jun 2016
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