111 citations · 204 across the 9 of their papers we have counts for
9 papers
Unpaired MRI Super Resolution with Contrastive Learning
Hao Li, Quanwei Liu, Jianan Liu +4
Magnetic resonance imaging (MRI) is crucial for enhancing diagnostic accuracy in clinical settings. However, the inherent long scan time of MRI restricts its widespread applicabili…
SMURF: Spatial Multi-Representation Fusion for 3D Object Detection with 4D Imaging Radar
Jianan Liu, Qiuchi Zhao, Weiyi Xiong +3
The 4D Millimeter wave (mmWave) radar is a promising technology for vehicle sensing due to its cost-effectiveness and operability in adverse weather conditions. However, the adopti…
LXL: LiDAR Excluded Lean 3D Object Detection with 4D Imaging Radar and Camera Fusion
Weiyi Xiong, Jianan Liu, Tao Huang +3
As an emerging technology and a relatively affordable device, the 4D imaging radar has already been confirmed effective in performing 3D object detection in autonomous driving. Nev…
GNN-PMB: A Simple but Effective Online 3D Multi-Object Tracker without Bells and Whistles
Jianan Liu, Liping Bai, Yuxuan Xia +3
Multi-object tracking (MOT) is among crucial applications in modern advanced driver assistance systems (ADAS) and autonomous driving (AD) systems. The global nearest neighbor (GNN)…
Unsupervised Representation Learning for 3D MRI Super Resolution with Degradation Adaptation
Jianan Liu, Hao Li, Tao Huang +6
High-resolution (HR) magnetic resonance imaging is critical in aiding doctors in their diagnoses and image-guided treatments. However, acquiring HR images can be time-consuming and…
Performance of a GPU- and Time-Efficient Pseudo 3D Network for Magnetic Resonance Image Super-Resolution and Motion Artifact Reduction
Hao Li, Jianan Liu, Marianne Schell +8
Shortening acquisition time and reducing motion artifacts are the most critical challenges in magnetic resonance imaging (MRI). Deep learning-based image restoration has emerged as…
Deep Instance Segmentation with Automotive Radar Detection Points
Jianan Liu, Weiyi Xiong, Liping Bai +4
Automotive radar provides reliable environmental perception in all-weather conditions with affordable cost, but it hardly supplies semantic and geometry information due to the spar…
Exploring Modality-shared Appearance Features and Modality-invariant Relation Features for Cross-modality Person Re-Identification
Nianchang Huang, Jianan Liu, Qiang Zhang +1
Most existing cross-modality person re-identification works rely on discriminative modality-shared features for reducing cross-modality variations and intra-modality variations. De…
Edge, Structure and Texture Refinement for Retrospective High Quality MRI Restoration using Deep Learning
Hao Li, Jianan Liu
22. Shortening acquisition time and reducing the motion-artifact are two of the most critical issues in MRI. As a promising solution, high-quality MRI image restoration provides a…