1.1k citations · 1.8k across the 7 of their papers we have counts for
7 papers
A Discriminative Learned CNN Embedding for Remote Sensing Image Scene Classification
Wen Wang, Lijun Du, Yinxing Gao +3
In this work, a discriminatively learned CNN embedding is proposed for remote sensing image scene classification. Our proposed siamese network simultaneously computes the classific…
Enhancing the Discriminative Feature Learning for Visible-Thermal Cross-Modality Person Re-Identification
Haijun Liu, Jian Cheng
Existing person re-identification has achieved great progress in the visible domain, capturing all the person images with visible cameras. However, in a 24-hour intelligent surveil…
Temporal Action Detection by Joint Identification-Verification
Wen Wang, Yongjian Wu, Haijun Liu +2
Temporal action detection aims at not only recognizing action category but also detecting start time and end time for each action instance in an untrimmed video. The key challenge…
Deep Continuous Conditional Random Fields with Asymmetric Inter-object Constraints for Online Multi-object Tracking
Hui Zhou, Wanli Ouyang, Jian Cheng +2
Online Multi-Object Tracking (MOT) is a challenging problem and has many important applications including intelligence surveillance, robot navigation and autonomous driving. In exi…
Additive Margin Softmax for Face Verification
Feng Wang, Weiyang Liu, Haijun Liu +1
In this paper, we propose a conceptually simple and geometrically interpretable objective function, i.e. additive margin Softmax (AM-Softmax), for deep face verification. In genera…
NormFace: L2 Hypersphere Embedding for Face Verification
Feng Wang, Xiang Xiang, Jian Cheng +1
Thanks to the recent developments of Convolutional Neural Networks, the performance of face verification methods has increased rapidly. In a typical face verification method, featu…
Regularizing Face Verification Nets For Pain Intensity Regression
Feng Wang, Xiang Xiang, Chang Liu +6
Limited labeled data are available for the research of estimating facial expression intensities. For instance, the ability to train deep networks for automated pain assessment is l…