Video-based person re-identification aims to match pedestrians from video sequences
across non-overlapping camera views. The key factor for video person re-identification is to …

Vision-based defect classification is an important technology to control the quality of product
in manufacturing system. As it is very hard to obtain enough labeled samples for model …

图神经网络(graph neural network, GNN) 是一种基于深度学习的图结构数据处理模型,
因良好的可解释性和对图结构数据强大的非线性拟合能力而受到研究者广泛关注. 随着GNN …

Unsupervised domain adaptation for person re-identification (Re-ID) suffers severe domain
discrepancies between source and target domains. To reduce the domain shift caused by …

Semi-supervised person re-identification (Re-ID) is an important approach for alleviating
annotation costs when learning to match person images across camera views. Most existing …

Some unsupervised approaches have been proposed recently for the person re-
identification (ReID) problem since annotations of samples across cameras are time …

Multi-target multi-camera tracking (MTMCT) targets to generate trajectories of the object that
appeared under multiple cameras automatically. MTMCT can be treated as a combination of …

Person re-identification (PRId) is one of the most challenging tasks in automated video
surveillance and has been an area of intense research spanning the past decade. PRId …

Localization and tracking in multi-player sports present significant challenges, particularly in
wide and crowded scenes where severe occlusions can occur. Traditional solutions relying …

Existing solutions to instance-level visual identification usually aim to learn faithful and
discriminative feature extractors from offline training data and directly use them for the …