57 citations · 64 across the 13 of their papers we have counts for
14 papers
SatSplat: Geometrically-Accurate Gaussian Splatting for Satellite Imagery
Shuang Song, Jiyong Kim, Rongjun Qin
High-resolution satellite imagery demands 3D reconstruction methods that deliver both speed and geometric accuracy. Recent adaptations of 3D Gaussian Splatting (3DGS) to satellite…
SatSplatDiff: Geometry-preserving generative refinement for high-fidelity satellite Gaussian Splatting
Jiyong Kim, Shuang Song, Rongjun Qin +1
Gaussian Splatting has been recently explored for satellite 3D reconstruction, demonstrating flexibility and efficiency in representing radiometrically diverse satellite scenes. Ho…
Olbedo: An Albedo and Shading Aerial Dataset for Large-Scale Outdoor Environments
Shuang Song, Debao Huang, Deyan Deng +4
Intrinsic image decomposition (IID) of outdoor scenes is crucial for relighting, editing, and understanding large-scale environments, but progress has been limited by the lack of r…
Synthetic Data Matters: Re-training with Geo-typical Synthetic Labels for Building Detection
Shuang Song, Yang Tang, Rongjun Qin
Deep learning has significantly advanced building segmentation in remote sensing, yet models struggle to generalize on data of diverse geographic regions due to variations in city…
A General Albedo Recovery Approach for Aerial Photogrammetric Images through Inverse Rendering
Shuang Song, Rongjun Qin
Modeling outdoor scenes for the synthetic 3D environment requires the recovery of reflectance/albedo information from raw images, which is an ill-posed problem due to the complicat…
Deep Learning Meets Satellite Images -- An Evaluation on Handcrafted and Learning-based Features for Multi-date Satellite Stereo Images
Shuang Song, Luca Morelli, Xinyi Wu +3
A critical step in the digital surface models(DSM) generation is feature matching. Off-track (or multi-date) satellite stereo images, in particular, can challenge the performance o…
Scalable Scene Modeling from Perspective Imaging: Physics-based Appearance and Geometry Inference
Shuang Song
3D scene modeling techniques serve as the bedrocks in the geospatial engineering and computer science, which drives many applications ranging from automated driving, terrain mappin…
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…
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…
A Novel Intrinsic Image Decomposition Method to Recover Albedo for Aerial Images in Photogrammetry Processing
Shuang Song, Rongjun Qin
Recovering surface albedos from photogrammetric images for realistic rendering and synthetic environments can greatly facilitate its downstream applications in VR/AR/MR and digital…
Vis2Mesh: Efficient Mesh Reconstruction from Unstructured Point Clouds of Large Scenes with Learned Virtual View Visibility
Shuang Song, Zhaopeng Cui, Rongjun Qin
We present a novel framework for mesh reconstruction from unstructured point clouds by taking advantage of the learned visibility of the 3D points in the virtual views and traditio…
A volumetric change detection framework using UAV oblique photogrammetry - A case study of ultra-high-resolution monitoring of progressive building collapse
Ningli Xu, Debao Huang, Shuang Song +5
In this paper, we present a case study that performs an unmanned aerial vehicle (UAV) based fine-scale 3D change detection and monitoring of progressive collapse performance of a b…
3D Reconstruction through Fusion of Cross-View Images
Rongjun Qin, Shuang Song, Xiao Ling +1
3D recovery from multi-stereo and stereo images, as an important application of the image-based perspective geometry, serves many applications in computer vision, remote sensing an…
A Comparison of Stereo-Matching Cost between Convolutional Neural Network and Census for Satellite Images
Bihe Chen, Rongjun Qin, Xu Huang +2
Stereo dense image matching can be categorized to low-level feature based matching and deep feature based matching according to their matching cost metrics. Census has been proofed…