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Torchreid: A Library for Deep Learning Person Re-Identification in Pytorch
Kaiyang Zhou, Tao Xiang
Person re-identification (re-ID), which aims to re-identify people across different camera views, has been significantly advanced by deep learning in recent years, particularly wit…
Learning Generalisable Omni-Scale Representations for Person Re-Identification
Kaiyang Zhou, Yongxin Yang, Andrea Cavallaro +1
An effective person re-identification (re-ID) model should learn feature representations that are both discriminative, for distinguishing similar-looking people, and generalisable,…
Few-Shot Learning with Global Class Representations
Tiange Luo, Aoxue Li, Tao Xiang +2
In this paper, we propose to tackle the challenging few-shot learning (FSL) problem by learning global class representations using both base and novel class training samples. In ea…
Goal-Driven Sequential Data Abstraction
Umar Riaz Muhammad, Yongxin Yang, Timothy M. Hospedales +2
Automatic data abstraction is an important capability for both benchmarking machine intelligence and supporting summarization applications. In the former one asks whether a machine…
Omni-Scale Feature Learning for Person Re-Identification
Kaiyang Zhou, Yongxin Yang, Andrea Cavallaro +1
As an instance-level recognition problem, person re-identification (ReID) relies on discriminative features, which not only capture different spatial scales but also encapsulate an…