2 citations · 3 across the 4 of their papers we have counts for
4 papers
Compass: Degradation-Simulated Reciprocal Learning with Lightweight Needle RWKV for Multimodal Crack Segmentation under Missing Modalities
Hui Liu, Chen Jia, Fan Shi +3
In multimodal crack segmentation for industrial facilities, the key challenge is preventing missing modalities from degrading pixel-level performance while maintaining low computat…
Noise-Robust Box-Supervised Infrared Small Target Detection via Physics-Inspired Soft Label Optimization
Xizhe Zhang, Fan Shi, Mianzhao Wang +3
Infrared small target detection (IRSTD) commonly relies on pixel-level mask supervision. Such annotations, however, are costly and inherently uncertain because infrared targets hav…
LIDAR: Lightweight Adaptive Cue-Aware Fusion Vision Mamba for Multimodal Segmentation of Structural Cracks
Hui Liu, Chen Jia, Fan Shi +4
Achieving pixel-level segmentation with low computational cost using multimodal data remains a key challenge in crack segmentation tasks. Existing methods lack the capability for a…
SCSegamba: Lightweight Structure-Aware Vision Mamba for Crack Segmentation in Structures
Hui Liu, Chen Jia, Fan Shi +2
Pixel-level segmentation of structural cracks across various scenarios remains a considerable challenge. Current methods encounter challenges in effectively modeling crack morpholo…