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Aug, 2022
SKDCGN: 使用cGAN源无关的对抗生成网络进行反事实知识蒸馏
SKDCGN: Source-free Knowledge Distillation of Counterfactual Generative Networks using cGANs
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Sameer Ambekar, Ankit Ankit, Diego van der Mast, Mark Alence, Matteo Tafuro
TL;DR
本文提出了一种使用预训练的CGN模型进行知识蒸馏的技术,以实现黑盒访问下的知识迁移。采用TinyGAN学习预训练的BigGAN,从而使生成图像更具属性,使分类器更具有不变性。
Abstract
With the usage of appropriate inductive biases,
counterfactual generative networks
(CGNs) can generate novel images from random combinations of shape, texture, and background manifolds. These images can be utilized to train an
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