Mingyao Ai

2.1k total citations · 1 hit paper
69 papers, 1.5k citations indexed

About

Mingyao Ai is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Geology. According to data from OpenAlex, Mingyao Ai has authored 69 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Computer Vision and Pattern Recognition, 32 papers in Aerospace Engineering and 26 papers in Geology. Recurrent topics in Mingyao Ai's work include Robotics and Sensor-Based Localization (29 papers), 3D Surveying and Cultural Heritage (26 papers) and Remote Sensing and LiDAR Applications (24 papers). Mingyao Ai is often cited by papers focused on Robotics and Sensor-Based Localization (29 papers), 3D Surveying and Cultural Heritage (26 papers) and Remote Sensing and LiDAR Applications (24 papers). Mingyao Ai collaborates with scholars based in China, Lithuania and United Kingdom. Mingyao Ai's co-authors include Qingwu Hu, Jiayuan Li, Pengcheng Zhao, Shaohua Wang, Ruofei Zhong, Shaohua Wang, Xujie Zhang, Haidong Li, Ju Zhang and Yongjun Zhang and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Geoscience and Remote Sensing and IEEE Transactions on Image Processing.

In The Last Decade

Mingyao Ai

64 papers receiving 1.5k citations

Hit Papers

RIFT: Multi-Modal Image Matching Based on Radiation-Varia... 2019 2026 2021 2023 2019 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. RIFT: Multi-Modal Image Matching Based on Radiation-Variation Insensitive Feature Transform
    2019 390 citations Jiayuan Li, Qingwu Hu et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Mingyao Ai China 20 838 704 374 363 257 69 1.5k
Li Yan China 23 501 0.6× 307 0.4× 260 0.7× 376 1.0× 352 1.4× 89 1.2k
Ulrich Thoennessen Germany 12 503 0.6× 618 0.9× 207 0.6× 325 0.9× 215 0.8× 50 1.1k
Wanshou Jiang China 20 533 0.6× 569 0.8× 660 1.8× 751 2.1× 177 0.7× 105 1.5k
Wolfgang Förstner Germany 15 520 0.6× 407 0.6× 451 1.2× 485 1.3× 116 0.5× 37 1.1k
Christoph Strecha Switzerland 20 2.0k 2.4× 1.2k 1.7× 728 1.9× 602 1.7× 250 1.0× 39 2.8k
Nicolas Paparoditis France 19 467 0.6× 316 0.4× 487 1.3× 727 2.0× 223 0.9× 76 1.4k
Caroline Baillard France 10 486 0.6× 191 0.3× 297 0.8× 394 1.1× 193 0.8× 23 888
Silvano Galliani Switzerland 9 1.7k 2.0× 387 0.5× 350 0.9× 389 1.1× 794 3.1× 14 2.3k
San Jiang China 18 461 0.6× 463 0.7× 438 1.2× 442 1.2× 54 0.2× 47 973
James Bethel United States 12 422 0.5× 479 0.7× 562 1.5× 574 1.6× 169 0.7× 38 1.5k

Countries citing papers authored by Mingyao Ai

Since Specialization
Citations

This map shows the geographic impact of Mingyao Ai's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mingyao Ai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingyao Ai more than expected).

Fields of papers citing papers by Mingyao Ai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mingyao Ai. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mingyao Ai. The network helps show where Mingyao Ai may publish in the future.

Co-authorship network of co-authors of Mingyao Ai

This figure shows the co-authorship network connecting the top 25 collaborators of Mingyao Ai. A scholar is included among the top collaborators of Mingyao Ai based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mingyao Ai. Mingyao Ai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Zhao, Pengcheng, et al.. (2025). 3D reconstruction for unconstrained image collections using Gaussian Splatting with foundation model. Geo-spatial Information Science. 1–14.
3.
Wang, Shaohua, et al.. (2025). CSNet: Change Selection of Activations and Pseudomasks for Image-Level Weakly Supervised Change Detection. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–20.
4.
Ai, Mingyao, et al.. (2025). A real-time image retrieval and localization method based on 360-degree panoramic visual feature maps. ISPRS Journal of Photogrammetry and Remote Sensing. 229. 351–365.
5.
Hu, Qingwu, et al.. (2025). FTransDeepLab: Multimodal Fusion Transformer-Based DeepLabv3+ for Remote Sensing Semantic Segmentation. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–18. 9 indexed citations
6.
Hu, Qingwu, et al.. (2024). Deep learning based method for 3D reconstruction of underground pipes in 3D GPR C-scan data. Tunnelling and Underground Space Technology. 150. 105819–105819. 12 indexed citations
7.
Hu, Qingwu, Mingyao Ai, Pengcheng Zhao, et al.. (2024). Weakly supervised 3D point cloud semantic segmentation for architectural heritage using teacher-guided consistency and contrast learning. Automation in Construction. 168. 105831–105831. 2 indexed citations
8.
Wang, Shaohua, et al.. (2024). Weakly Supervised Building Extraction From High-Resolution Remote Sensing Images Based on Building-Aware Clustering and Activation Refinement Network. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–15. 5 indexed citations
9.
Hu, Qingwu, et al.. (2024). A 3D urban scene reconstruction enhancement approach based on adaptive viewpoint selection of panoramic videos. The Photogrammetric Record. 39(185). 7–35. 1 indexed citations
10.
Hu, Qingwu, et al.. (2024). Category attention guided network for semantic segmentation of Fine-Resolution remote sensing images. International Journal of Applied Earth Observation and Geoinformation. 127. 103661–103661. 8 indexed citations
11.
12.
Hu, Qingwu, et al.. (2023). An Improved Probabilistic Roadmap Planning Method for Safe Indoor Flights of Unmanned Aerial Vehicles. Drones. 7(2). 92–92. 23 indexed citations
13.
Hu, Qingwu, et al.. (2023). ALS Point Cloud Semantic Segmentation Based on Graph Convolution and Transformer With Elevation Attention. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 17. 2877–2889. 4 indexed citations
14.
Hu, Qingwu, et al.. (2022). Real‐time fusion of multiple videos and 3D real scenes based on optimal viewpoint selection. Transactions in GIS. 27(1). 198–223. 3 indexed citations
15.
Zhao, Pengcheng, et al.. (2020). A Smooth Transition Algorithm for Adjacent Panoramic Viewpoints Using Matched Delaunay Triangular Patches. ISPRS International Journal of Geo-Information. 9(10). 596–596. 2 indexed citations
16.
Hu, Qingwu, et al.. (2020). An Approach of Identifying and Extracting Urban Commercial Areas Using the Nighttime Lights Satellite Imagery. Remote Sensing. 12(6). 1029–1029. 8 indexed citations
17.
Li, Jiayuan, Pengcheng Zhao, Qingwu Hu, & Mingyao Ai. (2019). Robust point cloud registration based on topological graph and Cauchy weighted lq-norm. ISPRS Journal of Photogrammetry and Remote Sensing. 160. 244–259. 40 indexed citations
18.
19.
Zhao, Pengcheng, Qingwu Hu, Shaohua Wang, Mingyao Ai, & Qingzhou Mao. (2018). Panoramic Image and Three-Axis Laser Scanner Integrated Approach for Indoor 3D Mapping. Remote Sensing. 10(8). 1269–1269. 8 indexed citations
20.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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