no code implementations • 9 May 2024 • Sy-Tuyen Ho, Koh Jun Hao, Keshigeyan Chandrasegaran, Ngoc-Bao Nguyen, Ngai-Man Cheung
Model Inversion (MI) attacks aim to reconstruct private training data by abusing access to machine learning models.
1 code implementation • 26 Jul 2023 • Milad Abdollahzadeh, Touba Malekzadeh, Christopher T. H. Teo, Keshigeyan Chandrasegaran, Guimeng Liu, Ngai-Man Cheung
In machine learning, generative modeling aims to learn to generate new data statistically similar to the training data distribution.
no code implementations • 4 Jul 2023 • Yunqing Zhao, Keshigeyan Chandrasegaran, Milad Abdollahzadeh, Chao Du, Tianyu Pang, Ruoteng Li, Henghui Ding, Ngai-Man Cheung
However, a major limitation of existing methods is that their knowledge preserving criteria consider only source domain/task and fail to consider target domain/adaptation in selecting source knowledge, casting doubt on their suitability for setups of different proximity between source and target domain.
1 code implementation • CVPR 2023 • Ngoc-Bao Nguyen, Keshigeyan Chandrasegaran, Milad Abdollahzadeh, Ngai-Man Cheung
Recently, several algorithms for MI have been proposed to improve the attack performance.
2 code implementations • 29 Oct 2022 • Yunqing Zhao, Keshigeyan Chandrasegaran, Milad Abdollahzadeh, Ngai-Man Cheung
However, a major limitation of existing methods is that their knowledge preserving criteria consider only source domain/source task, and they fail to consider target domain/adaptation task in selecting source model's knowledge, casting doubt on their suitability for setups of different proximity between source and target domain.
Ranked #1 on 10-shot image generation on Babies
1 code implementation • 24 Aug 2022 • Keshigeyan Chandrasegaran, Ngoc-Trung Tran, Alexander Binder, Ngai-Man Cheung
Visual counterfeits are increasingly causing an existential conundrum in mainstream media with rapid evolution in neural image synthesis methods.
1 code implementation • 29 Jun 2022 • Keshigeyan Chandrasegaran, Ngoc-Trung Tran, Yunqing Zhao, Ngai-Man Cheung
Critically, there is no effort to understand and resolve these contradictory findings, leaving the primal question -- to smooth or not to smooth a teacher network?
no code implementations • 29 Sep 2021 • Keshigeyan Chandrasegaran, Ngoc-Trung Tran, Yunqing Zhao, Ngai-Man Cheung
On the contrary, Shen et al. [2] claim that LS enlarges the distance between semantically similar classes; therefore a LS-trained teacher is compatible with KD.
1 code implementation • CVPR 2021 • Keshigeyan Chandrasegaran, Ngoc-Trung Tran, Ngai-Man Cheung
Our results prompt re-thinking of using high frequency Fourier spectrum decay attributes for CNN-generated image detection.