most citedRandom Erasing Data Augmentation

748 citations · 1.3k across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2018243 cited

Diagnose like a Radiologist: Attention Guided Convolutional Neural Network for Thorax Disease Classification

Qingji Guan, Yaping Huang, Zhun Zhong +3

This paper considers the task of thorax disease classification on chest X-ray images. Existing methods generally use the global image as input for network learning. Such a strategy…

cs.CV2017152 cited

Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)

Yifan Sun, Liang Zheng, Yi Yang +2

Employing part-level features for pedestrian image description offers fine-grained information and has been verified as beneficial for person retrieval in very recent literature. A…

cs.CV2017748 cited

Random Erasing Data Augmentation

Zhun Zhong, Liang Zheng, Guoliang Kang +2

In this paper, we introduce Random Erasing, a new data augmentation method for training the convolutional neural network (CNN). In training, Random Erasing randomly selects a recta…

cs.CV2017150 cited

Unsupervised Person Re-identification: Clustering and Fine-tuning

Hehe Fan, Liang Zheng, Yi Yang

The superiority of deeply learned pedestrian representations has been reported in very recent literature of person re-identification (re-ID). In this paper, we consider the more pr…

cs.CV201711 cited

A New Evaluation Protocol and Benchmarking Results for Extendable Cross-media Retrieval

Ruoyu Liu, Yao Zhao, Liang Zheng +2

This paper proposes a new evaluation protocol for cross-media retrieval which better fits the real-word applications. Both image-text and text-image retrieval modes are considered.…