Research on robust 3D imaging using single-photon LiDAR sensors, including depth and reflectivity estimation in photon-starved environments. Our work spans sensor fusion, underwater imaging, real-time 3D video reconstruction, human pose estimation, and advanced Bayesian and deep-learning approaches for TCSPC data.
Related Publications
DTU-Net: Learning Depth from ToF-LiDAR
IEEE TGRS, 2026
Graph Attention Networks for Multiscale SP LiDAR
IEEE TCI, 2025
Super Resolution Single-Photon Depth Imaging
Optics Express, 2025
Plug-and-Play Restoration of SP 3D Data
Optics Express, 2025
3D Target Detection for SP LiDAR
Optics Express, 2023
Real-Time 3D Videos from SP LiDAR
IEEE TCI, 2023
Pixels2Pose: Super-Resolution ToF for 3D Pose
Science Advances, 2022
Bayesian Unrolling for Robust 3D Reconstruction
IEEE JSTSP, 2022
Fast Task-Based Reconstruction for SP LiDAR
IEEE TCI, 2022
Robust Guided Bayesian Reconstruction for SP LiDAR
IEEE TCI, 2021
High-Speed Object Detection with SP ToF Sensor
Optics Express, 2021
Robust Real-Time 3D from SP LiDAR
Scientific Reports, 2021
Multi-Feature Fusion for SP LiDAR
Optics Express, 2021
High-Speed 3D via Hybrid-Mode SP LiDAR
Optica, 2020
Full Waveform LiDAR for Vehicle Detection
IEEE TVT, 2020
Ge-on-Si SPAD-Based LiDAR
Optics Express, 2020
Long-Range Depth Imaging Using SP LiDAR
Scientific Reports, 2019
3D Through Obscurants Using SP LiDAR
Optics Express, 2019
Range-Gated SP Depth Imaging
Optics Express, 2018
Camouflaged Target Detection from SP LiDAR
Optical Engineering, 2017
10km Range Depth Profiling Using SP LiDAR
Optics Express, 2017
Underwater 3D Imaging Using SP LiDAR
IEEE TCI, 2017