Human-centric visual tasks have attracted increasing research attention due to their
widespread applications. In this paper, we aim to learn a general human representation from …

Abstract Domain generalization person re-identification (DG ReID) aims to train a model on
source domains and generalize well on unseen domains. Vision Transformer usually yields …

Abstract The AI City Challenge's seventh edition emphasizes two domains at the intersection
of computer vision and artificial intelligence-retail business and Intelligent Traffic Systems …

The pre-training task is indispensable for the text-to-image person re-identification (T2I-
ReID) task. However, there are two underlying inconsistencies between these two tasks that …

In person re-identification (ReID), very recent researches have validated pre-training the
models on unlabelled person images is much better than on ImageNet. However, these …

Part feature learning is critical for fine-grained semantic understanding in vehicle re-
identification. However, existing approaches directly model part features and global …

A proposed method, Enhancement, integration, and Expansion, aims to activate the
representation of detailed features for occluded person re-identification. Region and context …

In the evolving landscape of surveillance and security applications, the task of person re-
identification (re-ID) has significant importance, but also presents notable difficulties. This …

In person re-identification (ReID) task, it is still challenging to learn discriminative
representation by deep learning, due to limited data. Generally speaking, the model will get …

Abstract Model pre-training is essential in human-centric perception. In this paper, we first
introduce masked image modeling (MIM) as a pre-training approach for this task. Upon …