activity
20152021
most citedF-SVM: Combination of Feature Transformation and SVM Learning via Convex Relaxation

5 citations · 12 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV20214 cited

Pseudo-ISP: Learning Pseudo In-camera Signal Processing Pipeline from A Color Image Denoiser

Yue Cao, Xiaohe Wu, Shuran Qi +3

The success of deep denoisers on real-world color photographs usually relies on the modeling of sensor noise and in-camera signal processing (ISP) pipeline. Performance drop will i…

eess.IV20203 cited

Unpaired Learning of Deep Image Denoising

Xiaohe Wu, Ming Liu, Yue Cao +2

We investigate the task of learning blind image denoising networks from an unpaired set of clean and noisy images. Such problem setting generally is practical and valuable consider…

cs.CV2018

Joint Representation and Truncated Inference Learning for Correlation Filter based Tracking

Yingjie Yao, Xiaohe Wu, Lei Zhang +2

Correlation filter (CF) based trackers generally include two modules, i.e., feature representation and on-line model adaptation. In existing off-line deep learning models for CF tr…

cs.CV2018

VITAL: VIsual Tracking via Adversarial Learning

Yibing Song, Chao Ma, Xiaohe Wu +6

The tracking-by-detection framework consists of two stages, i.e., drawing samples around the target object in the first stage and classifying each sample as the target object or as…

cs.LG20155 cited

F-SVM: Combination of Feature Transformation and SVM Learning via Convex Relaxation

Xiaohe Wu, Wangmeng Zuo, Yuanyuan Zhu +1

The generalization error bound of support vector machine (SVM) depends on the ratio of radius and margin, while standard SVM only considers the maximization of the margin but ignor…