16 citations · 27 across the 8 of their papers we have counts for
8 papers
PF-Trans: Physics-Embedded Frequency-Aware Transformer for Spectral Reconstruction
Yuzhe Gui, Tianzhu Liu, Yanfeng Gu +1
Snapshot Broadband Filter Array (BFA) imaging provides high light throughput for spectral reconstruction but introduces severe spectral aliasing due to complex modulation. Current…
CAMF-Det: Closure-Aware Multimodal Fusion for LiDAR-Camera 3D Object Detection on UAV Platforms
Yanze Jiang, Yanfeng Gu, Xian Li
Multimodal 3D object detection based on LiDAR and cameras has demonstrated excellent performance in ground-vehicle scenarios, but has not been explored for Unmanned Aerial Vehicle…
Illumination-Invariant Anomaly Detection for Sub-Canopy UAV Multispectral Point Clouds
Likun Chen, Yanfeng Gu, Xian Li
Unmanned Aerial Vehicle (UAV) multispectral point clouds (MPC) provide high-dimensional spatial-spectral data for sub-canopy target detection; however, their efficacy is significan…
Sub-Footprint Effect Correction in FW-LiDAR Point Clouds via Intra-Footprint Target Unmixing
Zhen Xiao, Yanfeng Gu, Xian Li
Sub-footprint target mixing within a laser footprint significantly increases LiDAR intensity uncertainty, especially in complex environments where heterogeneous materials inside on…
CroBIM-V: Memory-Quality Controlled Remote Sensing Referring Video Object Segmentation
H. Jiang, Y. Sun, Z. Dong +2
Remote sensing video referring object segmentation (RS-RVOS) is challenged by weak target saliency and severe visual information truncation in dynamic scenes, making it extremely d…
PhyDAE: Physics-Guided Degradation-Adaptive Experts for All-in-One Remote Sensing Image Restoration
Zhe Dong, Yuzhe Sun, Haochen Jiang +2
Remote sensing images inevitably suffer from various degradation factors during acquisition, including atmospheric interference, sensor limitations, and imaging conditions. These c…
Pillar-Voxel Fusion Network for 3D Object Detection in Airborne Hyperspectral Point Clouds
Yanze Jiang, Yanfeng Gu, Xian Li
Hyperspectral point clouds (HPCs) can simultaneously characterize 3D spatial and spectral information of ground objects, offering excellent 3D perception and target recognition cap…
LPRnet: A self-supervised registration network for LiDAR and photogrammetric point clouds
Chen Wang, Yanfeng Gu, Xian Li
LiDAR and photogrammetry are active and passive remote sensing techniques for point cloud acquisition, respectively, offering complementary advantages and heterogeneous. Due to the…