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Discovering Transferable Forensic Features for CNN-generated Images
  Detection

Discovering Transferable Forensic Features for CNN-generated Images Detection

24 August 2022
Keshigeyan Chandrasegaran
Ngoc-Trung Tran
Alexander Binder
Ngai-man Cheung
    AAML
ArXivPDFHTML

Papers citing "Discovering Transferable Forensic Features for CNN-generated Images Detection"

7 / 7 papers shown
Title
Frequency Masking for Universal Deepfake Detection
Frequency Masking for Universal Deepfake Detection
Chandler Timm C. Doloriel
Ngai-man Cheung
42
14
0
12 Jan 2024
Raising the Bar of AI-generated Image Detection with CLIP
Raising the Bar of AI-generated Image Detection with CLIP
D. Cozzolino
Giovanni Poggi
Riccardo Corvi
Matthias Nießner
L. Verdoliva
VLM
26
74
0
30 Nov 2023
Generalizable Synthetic Image Detection via Language-guided Contrastive Learning
Generalizable Synthetic Image Detection via Language-guided Contrastive Learning
Haiwei Wu
Jiantao Zhou
Shile Zhang
115
27
0
23 May 2023
Revisiting Label Smoothing and Knowledge Distillation Compatibility:
  What was Missing?
Revisiting Label Smoothing and Knowledge Distillation Compatibility: What was Missing?
Keshigeyan Chandrasegaran
Ngoc-Trung Tran
Yunqing Zhao
Ngai-man Cheung
83
41
0
29 Jun 2022
Improving the Fairness of Deep Generative Models without Retraining
Improving the Fairness of Deep Generative Models without Retraining
Shuhan Tan
Yujun Shen
Bolei Zhou
183
59
0
09 Dec 2020
A Style-Based Generator Architecture for Generative Adversarial Networks
A Style-Based Generator Architecture for Generative Adversarial Networks
Tero Karras
S. Laine
Timo Aila
282
10,354
0
12 Dec 2018
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,138
0
06 Jun 2015
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