Ningli Xu

I'm a 4th year Ph.D. student at The Ohio State University working with Rongjun Qin in Columbus, Ohio.

During my Ph.D. period, I worked on 3D reconstruction of multi-source data including satellite, aerial, UAV, ground-view images, 3D registration of cross-view/cross-source data, air-to-ground view sytnthesis.

Email / Scholar / ResearchGate / Github / Linkedin

Publications

Most my works are related to: Computer vision, Machine learning, Generative AI, NeRF, Diffusion. Some works are highlighted.

	Geospecific View Generation -- Geometry-Context Aware High-resolution Ground View Inference from Satellite Views Ningli Xu, Rongjun Qin ECCV 2024 (Oral Presentation, 200/8585, top 2.3%) paper \| dataset \| project page A diffusion-based method to perform ground-view synthesis conditioning on the weak building facades information from satellite images.
	Large-scale DSM registration via motion averaging Ningli Xu, Rongjun Qin ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2024 Best Paper Award (1/229) paper \| slides Want ICP (iterative closes point) be applied to terrain-scale DSMs (digital surface model) and even multiple noisy DSMs? Check out the proposed DSM-ICP, which applies a fast and exact nearest neighbor search method leveraging the grid structure of DSM.
	Multi-tiling neural radiance field (NeRF)—geometric assessment on large-scale aerial datasets Ningli Xu, Rongjun Qin, Debao Huang, Fabio Remondino The Photogrammetric Record , 2024 paper \| video \| code NeRF vs Multi-view stereo? We propose multi-camera tiling technique to enable NeRF on large-scale aerial datasets and further conduct experiment to compare their geometry reconstruction performance.
	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 ISPRS Open Journal of Photogrammetry and Remote Sensing , 2023 paper \| awesome-registration-papers Review and evaluation experiment of feature-based and ICP-based registration methods on photogrammetry and LiDAR data.
	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, Xiao Ling, Chris Strasbaugh, Alper Yilmaz, Halil Sezen, Rongjun Qin International Journal of Digital Earth , 2021 paper \| video Monitoring of progressive building collapse using photogrammetry technique.

Honors and Awards

Best Paper Award, ISPRS TC 1 Symposium, ChangSha, China, 2024 (1 out of 229)

Academic Services

Reviewer:

Neural Information Processing Systems (NeurPIS) 2024
British Machine Vision Conference (BMVC) 2024
ISPRS Journal of Photogrammetry and Remote Sensing
IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
IEEE Transactions on Image Processing (TIP)
Journal of Spatial Science

Last updated: 05/16/2024