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The Big Data Myth: Using Diffusion Models for Dataset Generation to
  Train Deep Detection Models

The Big Data Myth: Using Diffusion Models for Dataset Generation to Train Deep Detection Models

16 June 2023
Roy Voetman
Maya Aghaei
K. Dijkstra
    DiffM
ArXiv (abs)PDFHTML

Papers citing "The Big Data Myth: Using Diffusion Models for Dataset Generation to Train Deep Detection Models"

4 / 4 papers shown
Title
3D Human Reconstruction in the Wild with Synthetic Data Using Generative
  Models
3D Human Reconstruction in the Wild with Synthetic Data Using Generative Models
Yongtao Ge
Wenjia Wang
Yongfan Chen
Hao Chen
Chunhua Shen
3DH
72
8
0
17 Mar 2024
DF-GAN: A Simple and Effective Baseline for Text-to-Image Synthesis
DF-GAN: A Simple and Effective Baseline for Text-to-Image Synthesis
Ming Tao
Hao Tang
Leilei Gan
Xiaoyuan Jing
Bingkun Bao
Changsheng Xu
126
214
0
13 Aug 2020
Semantic Object Accuracy for Generative Text-to-Image Synthesis
Semantic Object Accuracy for Generative Text-to-Image Synthesis
Tobias Hinz
Stefan Heinrich
S. Wermter
EGVM
130
159
0
29 Oct 2019
YOLO9000: Better, Faster, Stronger
YOLO9000: Better, Faster, Stronger
Joseph Redmon
Ali Farhadi
VLMObjD
183
15,668
0
25 Dec 2016
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