551 citations · 2.1k across the 69 of their papers we have counts for
71 papers
Hybrid-Learning Video Moment Retrieval across Multi-Domain Labels
Weitong Cai, Jiabo Huang, Shaogang Gong
Video moment retrieval (VMR) is to search for a visual temporal moment in an untrimmed raw video by a given text query description (sentence). Existing studies either start from co…
Towards Generalisable Video Moment Retrieval: Visual-Dynamic Injection to Image-Text Pre-Training
Dezhao Luo, Jiabo Huang, Shaogang Gong +2
The correlation between the vision and text is essential for video moment retrieval (VMR), however, existing methods heavily rely on separate pre-training feature extractors for vi…
GridCLIP: One-Stage Object Detection by Grid-Level CLIP Representation Learning
Jiayi Lin, Shaogang Gong
A vision-language foundation model pretrained on very large-scale image-text paired data has the potential to provide generalizable knowledge representation for downstream visual r…
Exploring Semantic Attributes from A Foundation Model for Federated Learning of Disjoint Label Spaces
Shitong Sun, Chenyang Si, Guile Wu +1
Conventional centralised deep learning paradigms are not feasible when data from different sources cannot be shared due to data privacy or transmission limitation. To resolve this…
Video Activity Localisation with Uncertainties in Temporal Boundary
Jiabo Huang, Hailin Jin, Shaogang Gong +1
Current methods for video activity localisation over time assume implicitly that activity temporal boundaries labelled for model training are determined and precise. However, in un…
Rapid Person Re-Identification via Sub-space Consistency Regularization
Qingze Yin, Guanan Wang, Guodong Ding +3
Person Re-Identification (ReID) matches pedestrians across disjoint cameras. Existing ReID methods adopting real-value feature descriptors have achieved high accuracy, but they are…
Learning Unbiased Transferability for Domain Adaptation by Uncertainty Modeling
Jian Hu, Haowen Zhong, Junchi Yan +3
Domain adaptation (DA) aims to transfer knowledge learned from a labeled source domain to an unlabeled or a less labeled but related target domain. Ideally, the source and target d…
Feature-Distribution Perturbation and Calibration for Generalized Person ReID
Qilei Li, Jiabo Huang, Jian Hu +1
Person Re-identification (ReID) has been advanced remarkably over the last 10 years along with the rapid development of deep learning for visual recognition. However, the i.i.d. (i…
A Framework of Meta Functional Learning for Regularising Knowledge Transfer
Pan Li, Yanwei Fu, Shaogang Gong
Machine learning classifiers' capability is largely dependent on the scale of available training data and limited by the model overfitting in data-scarce learning tasks. To address…
Ranking Distance Calibration for Cross-Domain Few-Shot Learning
Pan Li, Shaogang Gong, Chengjie Wang +1
Recent progress in few-shot learning promotes a more realistic cross-domain setting, where the source and target datasets are from different domains. Due to the domain gap and disj…
Local-Global Associative Frame Assemble in Video Re-ID
Qilei Li, Jiabo Huang, Shaogang Gong
Noisy and unrepresentative frames in automatically generated object bounding boxes from video sequences cause significant challenges in learning discriminative representations in v…
Decentralised Person Re-Identification with Selective Knowledge Aggregation
Shitong Sun, Guile Wu, Shaogang Gong
Existing person re-identification (Re-ID) methods mostly follow a centralised learning paradigm which shares all training data to a collection for model learning. This paradigm is…
Cross-Sentence Temporal and Semantic Relations in Video Activity Localisation
Jiabo Huang, Yang Liu, Shaogang Gong +1
Video activity localisation has recently attained increasing attention due to its practical values in automatically localising the most salient visual segments corresponding to the…
Deep Clustering by Semantic Contrastive Learning
Jiabo Huang, Shaogang Gong
Whilst contrastive learning has recently brought notable benefits to deep clustering of unlabelled images by learning sample-specific discriminative visual features, its potential…
Unsupervised Noisy Tracklet Person Re-identification
Minxian Li, Xiatian Zhu, Shaogang Gong
Existing person re-identification (re-id) methods mostly rely on supervised model learning from a large set of person identity labelled training data per domain. This limits their…
Transfer Learning for Protein Structure Classification at Low Resolution
Alexander Hudson, Shaogang Gong
Structure determination is key to understanding protein function at a molecular level. Whilst significant advances have been made in predicting structure and function from amino ac…
Faster Person Re-Identification
Guan'an Wang, Shaogang Gong, Jian Cheng +1
Fast person re-identification (ReID) aims to search person images quickly and accurately. The main idea of recent fast ReID methods is the hashing algorithm, which learns compact b…
Unsupervised Transfer Learning with Self-Supervised Remedy
Jiabo Huang, Shaogang Gong
Generalising deep networks to novel domains without manual labels is challenging to deep learning. This problem is intrinsically difficult due to unpredictable changing nature of i…
Decentralised Learning from Independent Multi-Domain Labels for Person Re-Identification
Guile Wu, Shaogang Gong
Deep learning has been successful for many computer vision tasks due to the availability of shared and centralised large-scale training data. However, increasing awareness of priva…
Peer Collaborative Learning for Online Knowledge Distillation
Guile Wu, Shaogang Gong
Traditional knowledge distillation uses a two-stage training strategy to transfer knowledge from a high-capacity teacher model to a compact student model, which relies heavily on t…
Intra-Camera Supervised Person Re-Identification
Xiangping Zhu, Xiatian Zhu, Minxian Li +3
Existing person re-identification (re-id) methods mostly exploit a large set of cross-camera identity labelled training data. This requires a tedious data collection and annotation…
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…