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20142020
most citedDeep Transfer Learning for Person Re-identification

219 citations · 231 across the 5 of their papers we have counts for

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5 papers · 1 filter

cs.CV2020★ 1 cited

Boundary-sensitive Pre-training for Temporal Localization in Videos

Mengmeng Xu, Juan-Manuel Perez-Rua, Victor Escorcia +5

Many video analysis tasks require temporal localization thus detection of content changes. However, most existing models developed for these tasks are pre-trained on general video…

cs.CV2016★ 3 cited

Highly Efficient Regression for Scalable Person Re-Identification

Hanxiao Wang, Shaogang Gong, Tao Xiang

Existing person re-identification models are poor for scaling up to large data required in real-world applications due to: (1) Complexity: They employ complex models for optimal pe…

cs.CV2016★ 219 cited

Deep Transfer Learning for Person Re-identification

Mengyue Geng, Yaowei Wang, Tao Xiang +1

Person re-identification (Re-ID) poses a unique challenge to deep learning: how to learn a deep model with millions of parameters on a small training set of few or no labels. In th…

cs.CV2016★ 8 cited

Semantic Regularisation for Recurrent Image Annotation

Feng Liu, Tao Xiang, Timothy M. Hospedales +2

The "CNN-RNN" design pattern is increasingly widely applied in a variety of image annotation tasks including multi-label classification and captioning. Existing models use the weak…

cs.CV2014

Semantic Graph for Zero-Shot Learning

Zhen-Yong Fu, Tao Xiang, Shaogang Gong

Zero-shot learning aims to classify visual objects without any training data via knowledge transfer between seen and unseen classes. This is typically achieved by exploring a seman…