Mingye Xu

1.2k total citations
9 papers, 177 citations indexed

About

Mingye Xu is a scholar working on Computational Mechanics, Geology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Mingye Xu has authored 9 papers receiving a total of 177 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computational Mechanics, 7 papers in Geology and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Mingye Xu's work include 3D Shape Modeling and Analysis (8 papers), 3D Surveying and Cultural Heritage (7 papers) and Computer Graphics and Visualization Techniques (2 papers). Mingye Xu is often cited by papers focused on 3D Shape Modeling and Analysis (8 papers), 3D Surveying and Cultural Heritage (7 papers) and Computer Graphics and Visualization Techniques (2 papers). Mingye Xu collaborates with scholars based in China, Hong Kong and Cayman Islands. Mingye Xu's co-authors include Zhipeng Zhou, Yu Qiao, Junhao Zhang, Xiaojuan Qi, Mutian Xu, Yali Wang, Yu Qiao, Yihao Liu, Tong He and Kexue Fu and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Industrial Informatics and IEEE Transactions on Multimedia.

In The Last Decade

Mingye Xu

8 papers receiving 176 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mingye Xu China	6	144	113	64	61	51	9	177
Haoxi Ran China	3	116 0.8×	99 0.9×	54 0.8×	61 1.0×	40 0.8×	3	167
Gusi Te China	2	143 1.0×	109 1.0×	96 1.5×	89 1.5×	43 0.8×	2	229
Daeyun Shin United States	3	87 0.6×	46 0.4×	126 2.0×	15 0.2×	47 0.9×	5	166
Baorui Ma China	8	165 1.1×	54 0.5×	110 1.7×	19 0.3×	110 2.2×	17	237
André F. R. Guarda Portugal	9	188 1.3×	47 0.4×	187 2.9×	60 1.0×	161 3.2×	28	290
Christian Reiser Germany	4	107 0.7×	32 0.3×	163 2.5×	18 0.3×	147 2.9×	5	235
Jason Rock United States	5	72 0.5×	36 0.3×	227 3.5×	15 0.2×	50 1.0×	5	261
Ramesh Ashok Tabib India	7	36 0.3×	39 0.3×	131 2.0×	26 0.4×	14 0.3×	28	166
Renjiao Yi China	8	67 0.5×	29 0.3×	103 1.6×	11 0.2×	53 1.0×	25	176
Lior Yariv Israel	4	56 0.4×	22 0.2×	71 1.1×	9 0.1×	70 1.4×	5	108

Countries citing papers authored by Mingye Xu

Since Specialization

Citations

This map shows the geographic impact of Mingye Xu'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 Mingye Xu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingye Xu more than expected).

Fields of papers citing papers by Mingye Xu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mingye Xu. 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 Mingye Xu. The network helps show where Mingye Xu may publish in the future.

Co-authorship network of co-authors of Mingye Xu

This figure shows the co-authorship network connecting the top 25 collaborators of Mingye Xu. A scholar is included among the top collaborators of Mingye Xu 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 Mingye Xu. Mingye Xu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

9 of 9 papers shown

1.

Xu, Mingye, et al.. (2025). Unifying Adversarial Multi-Deconfounded Learning Paradigm for Fake News Detection. 2572–2583.

2.

Xu, Mingye, et al.. (2024). CP-Net: Contour-Perturbed Reconstruction Network for Self-Supervised Point Cloud Learning. IEEE Transactions on Multimedia. 26. 8799–8810. 6 indexed citations

3.

Xu, Mingye, et al.. (2023). Towards robustness and generalization of point cloud representation: A geometry coding method and a large-scale object-level dataset. Computational Visual Media. 10(1). 27–43. 3 indexed citations

4.

Xu, Mingye, Mutian Xu, Tong He, et al.. (2023). MM-3DScene: 3D Scene Understanding by Customizing Masked Modeling with Informative-Preserved Reconstruction and Self-Distilled Consistency. 4380–4390. 3 indexed citations

5.

Xu, Mingye, Yali Wang, Yihao Liu, Tong He, & Yu Qiao. (2023). CP3: Unifying Point Cloud Completion by Pretrain-Prompt-Predict Paradigm. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(8). 9583–9594. 12 indexed citations

6.

Fu, Kexue, et al.. (2022). Dual-Branch Deep Point Cloud Registration Framework for Unconstrained Rotation. IEEE Transactions on Industrial Informatics. 19(7). 7851–7861. 5 indexed citations

7.

Xu, Mingye, Zhipeng Zhou, Junhao Zhang, & Yu Qiao. (2021). Investigate Indistinguishable Points in Semantic Segmentation of 3D Point Cloud. Proceedings of the AAAI Conference on Artificial Intelligence. 35(4). 3047–3055. 13 indexed citations

8.

Xu, Mutian, Junhao Zhang, Zhipeng Zhou, et al.. (2021). Learning Geometry-Disentangled Representation for Complementary Understanding of 3D Object Point Cloud. Proceedings of the AAAI Conference on Artificial Intelligence. 35(4). 3056–3064. 76 indexed citations

9.

Xu, Mingye, Zhipeng Zhou, & Yu Qiao. (2020). Geometry Sharing Network for 3D Point Cloud Classification and Segmentation. Proceedings of the AAAI Conference on Artificial Intelligence. 34(7). 12500–12507. 59 indexed citations

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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