Robust and Accurate Object Detection Via Self-Knowledge Distillation
Weipeng Xu, Pengzhi Chu, Renhao Xie, Xiongziyan Xiao, Hongcheng Huang
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When deepfakes are widespread on chatting platforms, they are expected to be subject to heavy resizing and compressing steps. in this paper, we present a tensor-based representation of compressed and resized images. Tensor embeds DCT features computed on multi-scaled and multi-compressed versions of the input facial image. Moreover, a custom deep-architecture is designed and trained on the proposed representation. Experimental results show its pros and cons with respect to state-of-the-art methods.