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20052026
most citedRandom Erasing Data Augmentation

748 citations

Showing 2020 · cs.CVShow all

26 papers · 2 filters

cs.CV202014 cited

Hierarchical Representation via Message Propagation for Robust Model Fitting

Shuyuan Lin, Xing Wang, Guobao Xiao +2

In this paper, we propose a novel hierarchical representation via message propagation (HRMP) method for robust model fitting, which simultaneously takes advantages of both the cons…

cs.CV20202 cited

Robust Visual Tracking via Statistical Positive Sample Generation and Gradient Aware Learning

Lijian Lin, Haosheng Chen, Yanjie Liang +2

In recent years, Convolutional Neural Network (CNN) based trackers have achieved state-of-the-art performance on multiple benchmark datasets. Most of these trackers train a binary…

cs.CV202029 cited

Dual Semantic Fusion Network for Video Object Detection

Lijian Lin, Haosheng Chen, Honglun Zhang +4

Video object detection is a tough task due to the deteriorated quality of video sequences captured under complex environments. Currently, this area is dominated by a series of feat…

cs.CV20204 cited

Binarized Neural Architecture Search for Efficient Object Recognition

Hanlin Chen, Li'an Zhuo, Baochang Zhang +5

Traditional neural architecture search (NAS) has a significant impact in computer vision by automatically designing network architectures for various tasks. In this paper, binarize…

cs.CV20202 cited

Anti-Bandit Neural Architecture Search for Model Defense

Hanlin Chen, Baochang Zhang, Song Xue +4

Deep convolutional neural networks (DCNNs) have dominated as the best performers in machine learning, but can be challenged by adversarial attacks. In this paper, we defend against…

cs.CV2020

Learning Task-oriented Disentangled Representations for Unsupervised Domain Adaptation

Pingyang Dai, Peixian Chen, Qiong Wu +4

Unsupervised domain adaptation (UDA) aims to address the domain-shift problem between a labeled source domain and an unlabeled target domain. Many efforts have been made to address…