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Found 8 papers, 6 papers with code
A Survey on Generative Modeling with Limited Data, Few Shots, and Zero Shot
In machine learning, generative modeling aims to learn to generate new data statistically similar to the training data distribution.
AdAM: Few-Shot Image Generation via Adaptation-Aware Kernel Modulation
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.
Re-thinking Model Inversion Attacks Against Deep Neural Networks
Recently, several algorithms for MI have been proposed to improve the attack performance.
Few-shot Image Generation via Adaptation-Aware Kernel Modulation
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
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Discovering Transferable Forensic Features for CNN-generated Images Detection
Visual counterfeits are increasingly causing an existential conundrum in mainstream media with rapid evolution in neural image synthesis methods.
Revisiting Label Smoothing and Knowledge Distillation Compatibility: What was Missing?
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?
To Smooth or not to Smooth? On Compatibility between Label Smoothing and Knowledge Distillation
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.
A Closer Look at Fourier Spectrum Discrepancies for CNN-generated Images Detection
Our results prompt re-thinking of using high frequency Fourier spectrum decay attributes for CNN-generated image detection.
