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GANs-NQM: A Generative Adversarial Networks based No Reference Quality
  Assessment Metric for RGB-D Synthesized Views

GANs-NQM: A Generative Adversarial Networks based No Reference Quality Assessment Metric for RGB-D Synthesized Views

28 March 2019
Suiyi Ling
Jing Li
Junle Wang
P. Le Callet
ArXiv (abs)PDFHTML

Papers citing "GANs-NQM: A Generative Adversarial Networks based No Reference Quality Assessment Metric for RGB-D Synthesized Views"

3 / 3 papers shown
Few-Shot Object Detection in Real Life: Case Study on Auto-Harvest
Few-Shot Object Detection in Real Life: Case Study on Auto-Harvest
Kévin Riou
Jingwen Zhu
Suiyi Ling
Mathis Piquet
V. Truffault
P. Le Callet
187
8
0
05 Nov 2020
Quality Assessment of DIBR-synthesized views: An Overview
Quality Assessment of DIBR-synthesized views: An Overview
Shishun Tian
Lu Zhang
Wenbin Zou
Xia Li
Ting Su
L. Morin
Olivier Déforges
111
21
0
16 Nov 2019
Learning to Predict Image-based Rendering Artifacts with Respect to a
  Hidden Reference Image
Learning to Predict Image-based Rendering Artifacts with Respect to a Hidden Reference Image
Mojtaba Bemana
Joachim Keinert
K. Myszkowski
Michel Bätz
Matthias Ziegler
Hans-Peter Seidel
Tobias Ritschel
109
0
0
06 Dec 2018
1
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