no code implementations • 25 May 2024 • Hong-Shuo Chen, Yao Zhu, Suya You, Azad M. Madni, C. -C. Jay Kuo
Remarkably, our models are trained without backpropagation and achieve the best performance with fewer than 20G Multiply-Accumulate Operations (MACs).
no code implementations • 6 Jun 2023 • Yao Zhu, Xinyu Wang, Hong-Shuo Chen, Ronald Salloum, C. -C. Jay Kuo
A novel learning solution to image steganalysis based on the green learning paradigm, called Green Steganalyzer (GS), is proposed in this work.
no code implementations • 30 Apr 2022 • Hong-Shuo Chen, Shuowen Hu, Suya You, C. -C. Jay Kuo
Second, for discriminant features selection, DefakeHop uses an unsupervised approach while DefakeHop++ adopts a more effective approach with supervision, called the Discriminant Feature Test (DFT).
no code implementations • 7 Nov 2021 • Yao Zhu, Xinyu Wang, Hong-Shuo Chen, Ronald Salloum, C. -C. Jay Kuo
A novel method for detecting CNN-generated images, called Attentive PixelHop (or A-PixelHop), is proposed in this work.
no code implementations • 19 Oct 2021 • Hong-Shuo Chen, Kaitai Zhang, Shuowen Hu, Suya You, C. -C. Jay Kuo
A robust fake satellite image detection method, called Geo-DefakeHop, is proposed in this work.
no code implementations • 13 Apr 2021 • Kaitai Zhang, Bin Wang, Hong-Shuo Chen, Ye Wang, Shiyu Mou, C. -C. Jay Kuo
The main challenge of dynamic texture synthesis lies in how to maintain spatial and temporal consistency in synthesized videos.
1 code implementation • 11 Mar 2021 • Hong-Shuo Chen, Mozhdeh Rouhsedaghat, Hamza Ghani, Shuowen Hu, Suya You, C. -C. Jay Kuo
A light-weight high-performance Deepfake detection method, called DefakeHop, is proposed in this work.