activity
20192021
most citedRevisiting Knowledge Distillation: An Inheritance and Exploration Framework

3 citations · 4 across the 4 of their papers we have counts for

collaborators

7 papers

cs.LG20213 cited

Revisiting Knowledge Distillation: An Inheritance and Exploration Framework

Zhen Huang, Xu Shen, Jun Xing +6

Knowledge Distillation (KD) is a popular technique to transfer knowledge from a teacher model or ensemble to a student model. Its success is generally attributed to the privileged…

cs.CV2021

Dense Interaction Learning for Video-based Person Re-identification

Tianyu He, Xin Jin, Xu Shen +3

Video-based person re-identification (re-ID) aims at matching the same person across video clips. Efficiently exploiting multi-scale fine-grained features while building the struct…

cs.CV2020

Spatio-Temporal Inception Graph Convolutional Networks for Skeleton-Based Action Recognition

Zhen Huang, Xu Shen, Xinmei Tian +3

Skeleton-based human action recognition has attracted much attention with the prevalence of accessible depth sensors. Recently, graph convolutional networks (GCNs) have been widely…

cs.CV2019

Transform-Invariant Convolutional Neural Networks for Image Classification and Search

Xu Shen, Xinmei Tian, Anfeng He +2

Convolutional neural networks (CNNs) have achieved state-of-the-art results on many visual recognition tasks. However, current CNN models still exhibit a poor ability to be invaria…

cs.CV2019

Patch Reordering: a Novel Way to Achieve Rotation and Translation Invariance in Convolutional Neural Networks

Xu Shen, Xinmei Tian, Shaoyan Sun +1

Convolutional Neural Networks (CNNs) have demonstrated state-of-the-art performance on many visual recognition tasks. However, the combination of convolution and pooling operations…

cs.CV20191 cited

Continuous Dropout

Xu Shen, Xinmei Tian, Tongliang Liu +2

Dropout has been proven to be an effective algorithm for training robust deep networks because of its ability to prevent overfitting by avoiding the co-adaptation of feature detect…