Liang Zheng

Random Erasing Data Augmentation

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 re...

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

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...

Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification

Person re-identification (re-ID) models trained on one domain often fail to generalize well to another. In our attempt, we present a "learning via translation" framework. In the...

Towards Real-Time Multi-Object Tracking