551 citations · 2.1k across the 69 of their papers we have counts for
16 papers · 1 filter
Self-Referenced Deep Learning
Xu Lan, Xiatian Zhu, Shaogang Gong
Knowledge distillation is an effective approach to transferring knowledge from a teacher neural network to a student target network for satisfying the low-memory and fast running r…
Instance-level Sketch-based Retrieval by Deep Triplet Classification Siamese Network
Peng Lu, Hangyu Lin, Yanwei Fu +3
Sketch has been employed as an effective communicative tool to express the abstract and intuitive meanings of object. Recognizing the free-hand sketch drawing is extremely useful i…
Low-Resolution Face Recognition
Zhiyi Cheng, Xiatian Zhu, Shaogang Gong
Whilst recent face-recognition (FR) techniques have made significant progress on recognising constrained high-resolution web images, the same cannot be said on natively unconstrain…
Single-Label Multi-Class Image Classification by Deep Logistic Regression
Qi Dong, Xiatian Zhu, Shaogang Gong
The objective learning formulation is essential for the success of convolutional neural networks. In this work, we analyse thoroughly the standard learning objective functions for…
Vehicle Re-Identification in Context
Aytaç Kanacı, Xiatian Zhu, Shaogang Gong
Existing vehicle re-identification (re-id) evaluation benchmarks consider strongly artificial test scenarios by assuming the availability of high quality images and fine-grained ap…
Unsupervised Person Re-identification by Deep Learning Tracklet Association
Minxian Li, Xiatian Zhu, Shaogang Gong
Mostexistingpersonre-identification(re-id)methods relyon supervised model learning on per-camera-pair manually labelled pairwise training data. This leads to poor scalability in pr…
Deep Association Learning for Unsupervised Video Person Re-identification
Yanbei Chen, Xiatian Zhu, Shaogang Gong
Deep learning methods have started to dominate the research progress of video-based person re-identification (re-id). However, existing methods mostly consider supervised learning,…
Person Search by Multi-Scale Matching
Xu Lan, Xiatian Zhu, Shaogang Gong
We consider the problem of person search in unconstrained scene images. Existing methods usually focus on improving the person detection accuracy to mitigate negative effects impos…
Open Logo Detection Challenge
Hang Su, Xiatian Zhu, Shaogang Gong
Existing logo detection benchmarks consider artificial deployment scenarios by assuming that large training data with fine-grained bounding box annotations for each class are avail…
Person Re-Identification in Identity Regression Space
Hanxiao Wang, Xiatian Zhu, Shaogang Gong +1
Most existing person re-identification (re-id) methods are unsuitable for real-world deployment due to two reasons: Unscalability to large population size, and Inadaptability over…
Knowledge Distillation by On-the-Fly Native Ensemble
Xu Lan, Xiatian Zhu, Shaogang Gong
Knowledge distillation is effective to train small and generalisable network models for meeting the low-memory and fast running requirements. Existing offline distillation methods…
Imbalanced Deep Learning by Minority Class Incremental Rectification
Qi Dong, Shaogang Gong, Xiatian Zhu
Model learning from class imbalanced training data is a long-standing and significant challenge for machine learning. In particular, existing deep learning methods consider mostly…
Scalable Deep Learning Logo Detection
Hang Su, Shaogang Gong, Xiatian Zhu
Existing logo detection methods usually consider a small number of logo classes and limited images per class with a strong assumption of requiring tedious object bounding box annot…
Surveillance Face Recognition Challenge
Zhiyi Cheng, Xiatian Zhu, Shaogang Gong
Face recognition (FR) is one of the most extensively investigated problems in computer vision. Significant progress in FR has been made due to the recent introduction of the larger…
Transferable Joint Attribute-Identity Deep Learning for Unsupervised Person Re-Identification
Jingya Wang, Xiatian Zhu, Shaogang Gong +1
Most existing person re-identification (re-id) methods require supervised model learning from a separate large set of pairwise labelled training data for every single camera pair.…
Harmonious Attention Network for Person Re-Identification
Wei Li, Xiatian Zhu, Shaogang Gong
Existing person re-identification (re-id) methods either assume the availability of well-aligned person bounding box images as model input or rely on constrained attention selectio…