50 citations · 89 across the 15 of their papers we have counts for
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cs.CV2023
ShuffleMix: Improving Representations via Channel-Wise Shuffle of Interpolated Hidden States
Kangjun Liu, Ke Chen, Lihua Guo +2
Mixup style data augmentation algorithms have been widely adopted in various tasks as implicit network regularization on representation learning to improve model generalization, wh…
cs.CV2023★ 7 cited
Improving Deep Representation Learning via Auxiliary Learnable Target Coding
Kangjun Liu, Ke Chen, Kui Jia +1
Deep representation learning is a subfield of machine learning that focuses on learning meaningful and useful representations of data through deep neural networks. However, existin…
cs.CV2023★ 4 cited
Manifold-Aware Self-Training for Unsupervised Domain Adaptation on Regressing 6D Object Pose
Yichen Zhang, Jiehong Lin, Ke Chen +3
Domain gap between synthetic and real data in visual regression (e.g. 6D pose estimation) is bridged in this paper via global feature alignment and local refinement on the coarse c…