57 citations · 138 across the 50 of their papers we have counts for
7 papers · 1 filter
On the Transferability of Learning Models for Semantic Segmentation for Remote Sensing Data
Rongjun Qin, Guixiang Zhang, Yang Tang
Recent deep learning-based methods outperform traditional learning methods on remote sensing (RS) semantic segmentation/classification tasks. However, they require large training d…
A Critical Analysis of Internal Reliability for Uncertainty Quantification of Dense Image Matching in Multi-view Stereo
Debao Huang, Rongjun Qin
Nowadays, photogrammetrically derived point clouds are widely used in many civilian applications due to their low cost and flexibility in acquisition. Typically, photogrammetric po…
Multi-tiling Neural Radiance Field (NeRF) -- Geometric Assessment on Large-scale Aerial Datasets
Ningli Xu, Rongjun Qin, Debao Huang +1
Neural Radiance Fields (NeRF) offer the potential to benefit 3D reconstruction tasks, including aerial photogrammetry. However, the scalability and accuracy of the inferred geometr…
Mesh Conflation of Oblique Photogrammetric Models using Virtual Cameras and Truncated Signed Distance Field
Shuang Song, Rongjun Qin
Conflating/stitching 2.5D raster digital surface models (DSM) into a large one has been a running practice in geoscience applications, however, conflating full-3D mesh models, such…
Select-and-Combine (SAC): A Novel Multi-Stereo Depth Fusion Algorithm for Point Cloud Generation via Efficient Local Markov Netlets
Mostafa Elhashash, Rongjun Qin
Many practical systems for image-based surface reconstruction employ a stereo/multi-stereo paradigm, due to its ability to scale for large scenes and its ease of implementation for…
Large-scale and Efficient Texture Mapping Algorithm via Loopy Belief Propagation
Xiao ling, Rongjun Qin
Texture mapping as a fundamental task in 3D modeling has been well established for well-acquired aerial assets under consistent illumination, yet it remains a challenge when it is…
Point Cloud Registration for LiDAR and Photogrammetric Data: a Critical Synthesis and Performance Analysis on Classic and Deep Learning Algorithms
Ningli Xu, Rongjun Qin, Shuang Song
Recent advances in computer vision and deep learning have shown promising performance in estimating rigid/similarity transformation between unregistered point clouds of complex obj…