2.7k citations · 5.1k across the 51 of their papers we have counts for
51 papers
Optimizing Two-way Partial AUC with an End-to-end Framework
Zhiyong Yang, Qianqian Xu, Shilong Bao +3
The Area Under the ROC Curve (AUC) is a crucial metric for machine learning, which evaluates the average performance over all possible True Positive Rates (TPRs) and False Positive…
Rethinking Collaborative Metric Learning: Toward an Efficient Alternative without Negative Sampling
Shilong Bao, Qianqian Xu, Zhiyong Yang +2
The recently proposed Collaborative Metric Learning (CML) paradigm has aroused wide interest in the area of recommendation systems (RS) owing to its simplicity and effectiveness. T…
ADT-SSL: Adaptive Dual-Threshold for Semi-Supervised Learning
Zechen Liang, Yuan-Gen Wang, Wei Lu +1
Semi-Supervised Learning (SSL) has advanced classification tasks by inputting both labeled and unlabeled data to train a model jointly. However, existing SSL methods only consider…
Detecting Recolored Image by Spatial Correlation
Yushu Zhang, Nuo Chen, Shuren Qi +2
Image forensics, aiming to ensure the authenticity of the image, has made great progress in dealing with common image manipulation such as copy-move, splicing, and inpainting in th…
A Principled Design of Image Representation: Towards Forensic Tasks
Shuren Qi, Yushu Zhang, Chao Wang +2
Image forensics is a rising topic as the trustworthy multimedia content is critical for modern society. Like other vision-related applications, forensic analysis relies heavily on…
Defending against Model Stealing via Verifying Embedded External Features
Yiming Li, Linghui Zhu, Xiaojun Jia +3
Obtaining a well-trained model involves expensive data collection and training procedures, therefore the model is a valuable intellectual property. Recent studies revealed that adv…
Boosting Fast Adversarial Training with Learnable Adversarial Initialization
Xiaojun Jia, Yong Zhang, Baoyuan Wu +2
Adversarial training (AT) has been demonstrated to be effective in improving model robustness by leveraging adversarial examples for training. However, most AT methods are in face…
An Effective and Robust Detector for Logo Detection
Xiaojun Jia, Huanqian Yan, Yonglin Wu +3
In recent years, intellectual property (IP), which represents literary, inventions, artistic works, etc, gradually attract more and more people's attention. Particularly, with the…
Learning with Multiclass AUC: Theory and Algorithms
Zhiyong Yang, Qianqian Xu, Shilong Bao +2
The Area under the ROC curve (AUC) is a well-known ranking metric for problems such as imbalanced learning and recommender systems. The vast majority of existing AUC-optimization-b…
Poisoning Attack against Estimating from Pairwise Comparisons
Ke Ma, Qianqian Xu, Jinshan Zeng +2
As pairwise ranking becomes broadly employed for elections, sports competitions, recommendations, and so on, attackers have strong motivation and incentives to manipulate the ranki…
Arbitrarily Shaped Scene Text Detection: A Decade of Advances and Systematic Analysis
Pengwen Dai, Feiyang He, Chaolang Li +3
Scene text detection has become an important research area in computer vision. However, dynamic changes in scenes and the complex diversity of text appearances make accurate scene…
SIGAN: A Novel Image Generation Method for Solar Cell Defect Segmentation and Augmentation
Binyi Su, Zhong Zhou, Haiyong Chen +1
Solar cell electroluminescence (EL) defect segmentation is an interesting and challenging topic. Many methods have been proposed for EL defect detection, but these methods are stil…
A Survey of Orthogonal Moments for Image Representation: Theory, Implementation, and Evaluation
Shuren Qi, Yushu Zhang, Chao Wang +2
Image representation is an important topic in computer vision and pattern recognition. It plays a fundamental role in a range of applications towards understanding visual contents.…
Dense Attention Fluid Network for Salient Object Detection in Optical Remote Sensing Images
Qijian Zhang, Runmin Cong, Chongyi Li +5
Despite the remarkable advances in visual saliency analysis for natural scene images (NSIs), salient object detection (SOD) for optical remote sensing images (RSIs) still remains a…
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges
Moloud Abdar, Farhad Pourpanah, Sadiq Hussain +9
Uncertainty quantification (UQ) plays a pivotal role in reduction of uncertainties during both optimization and decision making processes. It can be applied to solve a variety of r…
Adv-watermark: A Novel Watermark Perturbation for Adversarial Examples
Xiaojun Jia, Xingxing Wei, Xiaochun Cao +1
Recent research has demonstrated that adding some imperceptible perturbations to original images can fool deep learning models. However, the current adversarial perturbations are u…
Single Image Super-Resolution via a Holistic Attention Network
Ben Niu, Weilei Wen, Wenqi Ren +6
Informative features play a crucial role in the single image super-resolution task. Channel attention has been demonstrated to be effective for preserving information-rich features…
Efficient Adversarial Attacks for Visual Object Tracking
Siyuan Liang, Xingxing Wei, Siyuan Yao +1
Visual object tracking is an important task that requires the tracker to find the objects quickly and accurately. The existing state-ofthe-art object trackers, i.e., Siamese based…
Face Super-Resolution Guided by 3D Facial Priors
Xiaobin Hu, Wenqi Ren, John LaMaster +5
State-of-the-art face super-resolution methods employ deep convolutional neural networks to learn a mapping between low- and high- resolution facial patterns by exploring local app…
Task-Feature Collaborative Learning with Application to Personalized Attribute Prediction
Zhiyong Yang, Qianqian Xu, Xiaochun Cao +1
As an effective learning paradigm against insufficient training samples, Multi-Task Learning (MTL) encourages knowledge sharing across multiple related tasks so as to improve the o…
Fast Stochastic Ordinal Embedding with Variance Reduction and Adaptive Step Size
Ke Ma, Jinshan Zeng, Qianqian Xu +3
Learning representation from relative similarity comparisons, often called ordinal embedding, gains rising attention in recent years. Most of the existing methods are based on semi…
iSplit LBI: Individualized Partial Ranking with Ties via Split LBI
Qianqian Xu, Xinwei Sun, Zhiyong Yang +3
Due to the inherent uncertainty of data, the problem of predicting partial ranking from pairwise comparison data with ties has attracted increasing interest in recent years. Howeve…
Identifying and Resisting Adversarial Videos Using Temporal Consistency
Xiaojun Jia, Xingxing Wei, Xiaochun Cao
Video classification is a challenging task in computer vision. Although Deep Neural Networks (DNNs) have achieved excellent performance in video classification, recent research sho…
Learning Personalized Attribute Preference via Multi-task AUC Optimization
Zhiyong Yang, Qianqian Xu, Xiaochun Cao +1
Traditionally, most of the existing attribute learning methods are trained based on the consensus of annotations aggregated from a limited number of annotators. However, the consen…