activity
20182022
most citedCE-Net: Context Encoder Network for 2D Medical Image Segmentation

2.3k citations · 2.4k across the 26 of their papers we have counts for

collaborators

36 papers

cs.CV20222 cited

Lifelong Person Re-Identification via Knowledge Refreshing and Consolidation

Chunlin Yu, Ye Shi, Zimo Liu +2

Lifelong person re-identification (LReID) is in significant demand for real-world development as a large amount of ReID data is captured from diverse locations over time and cannot…

cs.ET20221 cited

Electrical Tunable Spintronic Neuron with Trainable Activation Function

Yue Xin, Kang Zhou, Xuanyao Fong +3

Spintronic devices have been widely studied for the hardware realization of artificial neurons. The stochastic switching of magnetic tunnel junction driven by the spin torque is co…

cs.CV20221 cited

DearKD: Data-Efficient Early Knowledge Distillation for Vision Transformers

Xianing Chen, Qiong Cao, Yujie Zhong +3

Transformers are successfully applied to computer vision due to their powerful modeling capacity with self-attention. However, the excellent performance of transformers heavily dep…

cs.CV20224 cited

TransRAC: Encoding Multi-scale Temporal Correlation with Transformers for Repetitive Action Counting

Huazhang Hu, Sixun Dong, Yiqun Zhao +3

Counting repetitive actions are widely seen in human activities such as physical exercise. Existing methods focus on performing repetitive action counting in short videos, which is…

cs.CV20211 cited

MOS: A Low Latency and Lightweight Framework for Face Detection, Landmark Localization, and Head Pose Estimation

Yepeng Liu, Zaiwang Gu, Shenghua Gao +3

With the emergence of service robots and surveillance cameras, dynamic face recognition (DFR) in wild has received much attention in recent years. Face detection and head pose esti…

eess.IV20213 cited

Proxy-bridged Image Reconstruction Network for Anomaly Detection in Medical Images

Kang Zhou, Jing Li, Weixin Luo +6

Anomaly detection in medical images refers to the identification of abnormal images with only normal images in the training set. Most existing methods solve this problem with a sel…