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20182023
most citedAlleviating the Sample Selection Bias in Few-shot Learning by Removing Projection to the Centroid

8 citations · 11 across the 3 of their papers we have counts for

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5 papers · 1 filter

cs.CV2023★ 1 cited

Searching for the Fakes: Efficient Neural Architecture Search for General Face Forgery Detection

Xiao Jin, Xin-Yue Mu, Jing Xu

As the saying goes, "seeing is believing". However, with the development of digital face editing tools, we can no longer trust what we can see. Although face forgery detection has…

cs.CV2022★ 8 cited

Alleviating the Sample Selection Bias in Few-shot Learning by Removing Projection to the Centroid

Jing Xu, Xu Luo, Xinglin Pan +3

Few-shot learning (FSL) targets at generalization of vision models towards unseen tasks without sufficient annotations. Despite the emergence of a number of few-shot learning metho…

cs.CV2021

AFINet: Attentive Feature Integration Networks for Image Classification

Xinglin Pan, Jing Xu, Yu Pan +4

Convolutional Neural Networks (CNNs) have achieved tremendous success in a number of learning tasks including image classification. Recent advanced models in CNNs, such as ResNets,…

cs.CV2021

MultiFace: A Generic Training Mechanism for Boosting Face Recognition Performance

Jing Xu, Tszhang Guo, Yong Xu +2

Deep Convolutional Neural Networks (DCNNs) and their variants have been widely used in large scale face recognition(FR) recently. Existing methods have achieved good performance on…

cs.CV2018

Compressing Recurrent Neural Networks with Tensor Ring for Action Recognition

Yu Pan, Jing Xu, Maolin Wang +4

Recurrent Neural Networks (RNNs) and their variants, such as Long-Short Term Memory (LSTM) networks, and Gated Recurrent Unit (GRU) networks, have achieved promising performance in…