4 citations · 7 across the 12 of their papers we have counts for
13 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, Ronjgun Qin
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…