Tianrui Liu

Orcid: 0000-0001-7926-3310

Affiliations:
  • National University of Defense Technology (NUDT), College of Computer Science and Technology, Changsha, China
  • Imperial College London (ICL), Department of Computing, Department of Electrical and Electronic Engineering, UK (PhD 2019)


According to our database1, Tianrui Liu authored at least 22 papers between 2016 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2025
Sampling Enhanced Contrastive Multi-View Remote Sensing Data Clustering With Long-Short Range Information Mining.
IEEE Trans. Knowl. Data Eng., September, 2025

A Lightweight Deep Exclusion Unfolding Network for Single Image Reflection Removal.
IEEE Trans. Pattern Anal. Mach. Intell., June, 2025

Category Alignment Mechanism for Few-Shot Image Classification.
IEEE Trans. Neural Networks Learn. Syst., April, 2025

SMILENet: Unleashing Extra-Large Capacity Image Steganography via a Synergistic Mosaic InvertibLE Hiding Network.
CoRR, March, 2025

A Lightweight Deep Exclusion Unfolding Network for Single Image Reflection Removal.
CoRR, March, 2025

Recalling Unknowns Without Losing Precision: An Effective Solution to Large Model-Guided Open World Object Detection.
IEEE Trans. Image Process., 2025

EASEMVC: Efficient Dual Selection Mechanism for Deep Multi-View Clustering.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024
DeMPAA: Deployable Multi-Mini-Patch Adversarial Attack for Remote Sensing Image Classification.
IEEE Trans. Geosci. Remote. Sens., 2024

Alleviate Anchor-Shift: Explore Blind Spots with Cross-View Reconstruction for Incomplete Multi-View Clustering.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

View Gap Matters: Cross-view Topology and Information Decoupling for Multi-view Clustering.
Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

DURRNET: Deep Unfolded Single Image Reflection Removal Network with Joint Prior.
Proceedings of the IEEE International Conference on Acoustics, 2024

2022
MulViMotion: Shape-Aware 3D Myocardial Motion Tracking From Multi-View Cardiac MRI.
IEEE Trans. Medical Imaging, 2022

2021
Coupled Network for Robust Pedestrian Detection With Gated Multi-Layer Feature Extraction and Deformable Occlusion Handling.
IEEE Trans. Image Process., 2021

Detecting Hypo-plastic Left Heart Syndrome in Fetal Ultrasound via Disease-Specific Atlas Maps.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

2020
Gated Multi-Layer Convolutional Feature Extraction Network for Robust Pedestrian Detection.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2018
Faster R-CNN for Robust Pedestrian Detection Using Semantic Segmentation Network.
Frontiers Neurorobotics, 2018

SAM-RCNN: Scale-Aware Multi-Resolution Multi-Channel Pedestrian Detection.
Proceedings of the British Machine Vision Conference 2018, 2018

2017
Fast Head-Shoulder Proposal for Scare-Aware Pedestrian Detection.
Proceedings of the 10th International Conference on PErvasive Technologies Related to Assistive Environments, 2017

Enhanced pedestrian detection using deep learning based semantic image segmentation.
Proceedings of the 22nd International Conference on Digital Signal Processing, 2017

SRHRF+: Self-Example Enhanced Single Image Super-Resolution Using Hierarchical Random Forests.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2017

2016
Human Detection from Ground Truth Cameras through Combined Use of Histogram of Oriented Gradients and Body Part Models.
Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016), 2016

Fast head-shoulder proposal for deformable part model based pedestrian detection.
Proceedings of the 2016 IEEE International Conference on Digital Signal Processing, 2016


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