no code implementations • 7 Jun 2023 • Libin Wang, Han Hu, Qisen Shang, Bo Xu, Qing Zhu
The lack of fa\c{c}ade structures in photogrammetric mesh models renders them inadequate for meeting the demands of intricate applications.
no code implementations • 12 Apr 2023 • Haojia Yu, Han Hu, Bo Xu, Qisen Shang, Zhendong Wang, Qing Zhu
Most urban applications necessitate building footprints in the form of concise vector graphics with sharp boundaries rather than pixel-wise raster images.
no code implementations • 30 Mar 2023 • Qisen Shang, Han Hu, Haojia Yu, Bo Xu, Libin Wang, Qing Zhu
Experimental results on publicly available fa\c{c}ade image and 3D model datasets demonstrate that our method yields superior results and effectively addresses issues associated with flawed textures.
no code implementations • 22 Jan 2022 • Han Hu, Xinrong Liang, Yulin Ding, Qisen Shang, Bo Xu, Xuming Ge, Min Chen, Ruofei Zhong, Qing Zhu
Unfortunately, the large amount of interactive sample labeling efforts has dramatically hindered the application of deep learning methods, especially for 3D modeling tasks, which require heterogeneous samples.
1 code implementation • 3 Oct 2021 • Li Chen, Yulin Ding, Saeid Pirasteh, Han Hu, Qing Zhu, Haowei Zeng, Haojia Yu, Qisen Shang, Yongfei Song
Then, the critical problem is that in each block with limited samples, conducting training and testing a model is impossible for a satisfactory LSM prediction, especially in dangerous mountainous areas where landslide surveying is expensive.
1 code implementation • 23 Nov 2020 • Qing Zhu, Qisen Shang, Han Hu, Haojia Yu, Ruofei Zhong
Finally, the completed rendered image is deintegrated to the original texture atlas and the triangles for the vehicles are also flattened for improved meshes.