Any computer vision application development starts off by acquiring images and data, then
preprocessing and pattern recognition steps to perform a task. When the acquired images …

Visible-infrared person re-identification (VI-ReID) aims to match a specific person from a
gallery of images captured from non-overlapping visible and infrared cameras. Most works …

To calculate the model accuracy on a computer vision task, eg, object recognition, we
usually require a test set composing of test samples and their ground truth labels. Whilst …

Unsupervised domain adaptation (UDA) methods for person re-identification (re-ID) aim at
transferring re-ID knowledge from labeled source data to unlabeled target data. Among …

Domain generalizable person re-identification (DG ReID) is a challenging problem, because
the trained model is often not generalizable to unseen target domains with different …

Unsupervised domain adaptation (UDA) aims at adapting the model trained on a labeled
source-domain dataset to an unlabeled target-domain dataset. The task of UDA on open-set …

Unsupervised person re-identification (re-ID) remains a challenging task. While extensive
research has focused on the framework design and loss function, this paper shows that …

Due to the domain shift between source dataset and target dataset, most of the existing
person re-identification (PRID) algorithms trained by a supervised learning framework often …

Currently, with the rapid development of deep learning, many breakthroughs have been
made in the field of facial expression recognition (FER). However, according to our prior …

This article aims to use graphic engines to simulate a large number of training data that have
free annotations and possibly strongly resemble to real-world data. Between synthetic and …