551 citations · 2.1k across the 69 of their papers we have counts for
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Characteristic Regularisation for Super-Resolving Face Images
Zhiyi Cheng, Xiatian Zhu, Shaogang Gong
Existing facial image super-resolution (SR) methods focus mostly on improving artificially down-sampled low-resolution (LR) imagery. Such SR models, although strong at handling art…
Intra-Camera Supervised Person Re-Identification: A New Benchmark
Xiangping Zhu, Xiatian Zhu, Minxian Li +2
Existing person re-identification (re-id) methods rely mostly on a large set of inter-camera identity labelled training data, requiring a tedious data collection and annotation pro…
Zero-Shot Crowd Behavior Recognition
Xun Xu, Shaogang Gong, Timothy Hospedales
Understanding crowd behavior in video is challenging for computer vision. There have been increasing attempts on modeling crowded scenes by introducing ever larger property ontolog…
Universal Person Re-Identification
Xu Lan, Xiatian Zhu, Shaogang Gong
Most state-of-the-art person re-identification (re-id) methods depend on supervised model learning with a large set of cross-view identity labelled training data. Even worse, such…
Unsupervised Deep Learning by Neighbourhood Discovery
Jiabo Huang, Qi Dong, Shaogang Gong +1
Deep convolutional neural networks (CNNs) have demonstrated remarkable success in computer vision by supervisedly learning strong visual feature representations. However, training…
Unsupervised Person Re-identification by Soft Multilabel Learning
Hong-Xing Yu, Wei-Shi Zheng, Ancong Wu +3
Although unsupervised person re-identification (RE-ID) has drawn increasing research attentions due to its potential to address the scalability problem of supervised RE-ID models,…
Unsupervised Tracklet Person Re-Identification
Minxian Li, Xiatian Zhu, Shaogang Gong
Most existing person re-identification (re-id) methods rely on supervised model learning on per-camera-pair manually labelled pairwise training data. This leads to poor scalability…