401 citations · 1.6k across the 64 of their papers we have counts for
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Batch Normalization with Enhanced Linear Transformation
Yuhui Xu, Lingxi Xie, Cihang Xie +5
Batch normalization (BN) is a fundamental unit in modern deep networks, in which a linear transformation module was designed for improving BN's flexibility of fitting complex data…
Shape-Texture Debiased Neural Network Training
Yingwei Li, Qihang Yu, Mingxing Tan +5
Shape and texture are two prominent and complementary cues for recognizing objects. Nonetheless, Convolutional Neural Networks are often biased towards either texture or shape, dep…
Smooth Adversarial Training
Cihang Xie, Mingxing Tan, Boqing Gong +2
It is commonly believed that networks cannot be both accurate and robust, that gaining robustness means losing accuracy. It is also generally believed that, unless making networks…
Neural Architecture Search for Lightweight Non-Local Networks
Yingwei Li, Xiaojie Jin, Jieru Mei +7
Non-Local (NL) blocks have been widely studied in various vision tasks. However, it has been rarely explored to embed the NL blocks in mobile neural networks, mainly due to the fol…
PatchAttack: A Black-box Texture-based Attack with Reinforcement Learning
Chenglin Yang, Adam Kortylewski, Cihang Xie +2
Patch-based attacks introduce a perceptible but localized change to the input that induces misclassification. A limitation of current patch-based black-box attacks is that they per…