748 citations · 1.3k across the 20 of their papers we have counts for
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Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification
Weijian Deng, Liang Zheng, Qixiang Ye +3
Person re-identification (re-ID) models trained on one domain often fail to generalize well to another. In our attempt, we present a "learning via translation" framework. In the ba…
EraseReLU: A Simple Way to Ease the Training of Deep Convolution Neural Networks
Xuanyi Dong, Guoliang Kang, Kun Zhan +1
For most state-of-the-art architectures, Rectified Linear Unit (ReLU) becomes a standard component accompanied with each layer. Although ReLU can ease the network training to an ex…
Random Erasing Data Augmentation
Zhun Zhong, Liang Zheng, Guoliang Kang +2
In this paper, we introduce Random Erasing, a new data augmentation method for training the convolutional neural network (CNN). In training, Random Erasing randomly selects a recta…
PatchShuffle Regularization
Guoliang Kang, Xuanyi Dong, Liang Zheng +1
This paper focuses on regularizing the training of the convolutional neural network (CNN). We propose a new regularization approach named ``PatchShuffle`` that can be adopted in an…