47 citations · 70 across the 10 of their papers we have counts for
10 papers
MHL: Mutual Mask Mix with High-Low Level Feature Consistency for Semi-Supervised Medical Image Segmentation
Yajun Liu, Zenghui Zhang, Jiang Yue +2
Data augmentation methods inspired by CutMix have demonstrated significant potential in recent semi-supervised medical image segmentation tasks. However, these approaches often app…
Grid-Reg: Detector-Free Gridized Feature Learning and Matching for Large-Scale SAR-Optical Image Registration
Xiaochen Wei, Weiwei Guo, Zenghui Zhang +1
It is highly challenging to register large-scale, heterogeneous SAR and optical images, particularly across platforms, due to significant geometric, radiometric, and temporal diffe…
UMSPU: Universal Multi-Size Phase Unwrapping via Mutual Self-Distillation and Adaptive Boosting Ensemble Segmenters
Lintong Du, Huazhen Liu, Yijia Zhang +4
Spatial phase unwrapping is a key technique for extracting phase information to obtain 3D morphology and other features. Modern industrial measurement scenarios demand high precisi…
Spatio-Temporal Point Process for Multiple Object Tracking
Tao Wang, Kean Chen, Weiyao Lin +4
Multiple Object Tracking (MOT) focuses on modeling the relationship of detected objects among consecutive frames and merge them into different trajectories. MOT remains a challengi…
Exploring Resolution and Degradation Clues as Self-supervised Signal for Low Quality Object Detection
Ziteng Cui, Yingying Zhu, Lin Gu +5
Image restoration algorithms such as super resolution (SR) are indispensable pre-processing modules for object detection in low quality images. Most of these algorithms assume the…
Multitask AET with Orthogonal Tangent Regularity for Dark Object Detection
Ziteng Cui, Guo-Jun Qi, Lin Gu +3
Dark environment becomes a challenge for computer vision algorithms owing to insufficient photons and undesirable noise. To enhance object detection in a dark environment, we propo…
Explainable Analysis of Deep Learning Methods for SAR Image Classification
Shenghan Su, Ziteng Cui, Weiwei Guo +2
Deep learning methods exhibit outstanding performance in synthetic aperture radar (SAR) image interpretation tasks. However, these are black box models that limit the comprehension…
RestoreDet: Degradation Equivariant Representation for Object Detection in Low Resolution Images
Ziteng Cui, Yingying Zhu, Lin Gu +5
Image restoration algorithms such as super resolution (SR) are indispensable pre-processing modules for object detection in degraded images. However, most of these algorithms assum…
Integrated Sensing and Communications for V2I Networks: Dynamic Predictive Beamforming for Extended Vehicle Targets
Zhen Du, Fan Liu, Weijie Yuan +4
We investigate sensing-assisted predictive beamforming schemes for vehicle-to-infrastructure (V2I) communication by exploiting the integrated sensing and communication (ISAC) funct…
Spectral Compressive Sensing with Model Selection
Zhenqi Lu, Rendong Ying, Sumxin Jiang +3
The performance of existing approaches to the recovery of frequency-sparse signals from compressed measurements is limited by the coherence of required sparsity dictionaries and th…