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 …

Employing part-level features offers fine-grained information for pedestrian image
description. A prerequisite of part discovery is that each part should be well located. Instead …

Deep learning has produced state-of-the-art results for a variety of tasks. While such
approaches for supervised learning have performed well, they assume that training and …

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 baseline, we …

This paper considers the domain adaptive person re-identification (re-ID) problem: learning
a re-ID model from a labeled source domain and an unlabeled target domain. Conventional …

Image-to-image translation (I2I) aims to transfer images from a source domain to a target
domain while preserving the content representations. I2I has drawn increasing attention and …

The challenge of unsupervised person re-identification (ReID) lies in learning discriminative
features without true labels. This paper formulates unsupervised person ReID as a multi …

Cross-modality person re-identification is a challenging task due to large cross-modality
discrepancy and intra-modality variations. Currently, most existing methods focus on …

Abstract Domain adaptation in person re-identification (re-ID) has always been a
challenging task. In this work, we explore how to harness the similar natural characteristics …