As a promising area in machine learning, multi-task learning (MTL) aims to improve the
performance of multiple related learning tasks by leveraging useful information among them …

Multi-Task Learning (MTL) is a learning paradigm in machine learning and its aim is to
leverage useful information contained in multiple related tasks to help improve the …

This paper contributes a new high quality dataset for person re-identification, named" Market-
1501". Generally, current datasets: 1) are limited in scale; 2) consist of hand-drawn bboxes …

Person re-identification (ReID) is an important task in wide area video surveillance which
focuses on identifying people across different cameras. Recently, deep learning networks …

Person re-identification (re-ID) has become increasingly popular in the community due to its
application and research significance. It aims at spotting a person of interest in other …

Multi-task learning in Convolutional Networks has displayed remarkable success in the field
of recognition. This success can be largely attributed to learning shared representations …

This paper considers person re-identification (re-id) in videos. We introduce a new video re-
id dataset, named M otion A nalysis and R e-identification S et (MARS), a video extension of …

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 …

In this paper, we address the problem of person re-identification, which refers to associating
the persons captured from different cameras. We propose a simple yet effective human part …

Person re-identification (re-ID) and attribute recognition share a common target at learning
pedestrian descriptions. Their difference consists in the granularity. Most existing re-ID …