42 citations · 164 across the 13 of their papers we have counts for
5 papers · 1 filter
Volumetric Medical Image Segmentation: A 3D Deep Coarse-to-fine Framework and Its Adversarial Examples
Yingwei Li, Zhuotun Zhu, Yuyin Zhou +4
Although deep neural networks have been a dominant method for many 2D vision tasks, it is still challenging to apply them to 3D tasks, such as medical image segmentation, due to th…
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…
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…
Adversarial Attacks on Monocular Depth Estimation
Ziqi Zhang, Xinge Zhu, Yingwei Li +2
Recent advances of deep learning have brought exceptional performance on many computer vision tasks such as semantic segmentation and depth estimation. However, the vulnerability o…
CAKES: Channel-wise Automatic KErnel Shrinking for Efficient 3D Networks
Qihang Yu, Yingwei Li, Jieru Mei +2
3D Convolution Neural Networks (CNNs) have been widely applied to 3D scene understanding, such as video analysis and volumetric image recognition. However, 3D networks can easily l…