Xiaoyang Lyu

661 total citations
12 papers, 354 citations indexed

About

Xiaoyang Lyu is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Computer Graphics and Computer-Aided Design. According to data from OpenAlex, Xiaoyang Lyu has authored 12 papers receiving a total of 354 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Vision and Pattern Recognition, 6 papers in Computational Mechanics and 5 papers in Computer Graphics and Computer-Aided Design. Recurrent topics in Xiaoyang Lyu's work include Advanced Vision and Imaging (8 papers), 3D Shape Modeling and Analysis (6 papers) and Computer Graphics and Visualization Techniques (5 papers). Xiaoyang Lyu is often cited by papers focused on Advanced Vision and Imaging (8 papers), 3D Shape Modeling and Analysis (6 papers) and Computer Graphics and Visualization Techniques (5 papers). Xiaoyang Lyu collaborates with scholars based in Hong Kong, China and United States. Xiaoyang Lyu's co-authors include Yong Liu, Lina Liu, Mengmeng Wang, Xinxin Chen, Xin Kong, Liang Liu, Yi Yuan, Liangjun Zhang, Xibin Song and Xiaojuan Qi and has published in prestigious journals such as IEEE Robotics and Automation Letters, Rare & Special e-Zone (The Hong Kong University of Science and Technology) and Proceedings of the AAAI Conference on Artificial Intelligence.

In The Last Decade

Xiaoyang Lyu

10 papers receiving 342 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Xiaoyang Lyu Hong Kong	7	317	154	71	40	30	12	354
Jiaxiong Qiu China	4	247 0.8×	101 0.7×	89 1.3×	20 0.5×	18 0.6×	9	270
Kevin Matzen Israel	7	347 1.1×	89 0.6×	101 1.4×	70 1.8×	5 0.2×	7	377
Zhelun Shen China	8	310 1.0×	76 0.5×	65 0.9×	15 0.4×	11 0.4×	16	340
Guilherme V. Cavalheiro United States	3	277 0.9×	109 0.7×	131 1.8×	10 0.3×	11 0.4×	4	303
Yevhen Kuznietsov Switzerland	3	432 1.4×	237 1.5×	116 1.6×	8 0.2×	17 0.6×	4	459
Yidan Feng China	7	248 0.8×	91 0.6×	15 0.2×	51 1.3×	21 0.7×	19	316
Laurent Caraffa France	6	416 1.3×	236 1.5×	18 0.3×	28 0.7×	5 0.2×	12	461
Shuling Wang China	5	194 0.6×	62 0.4×	97 1.4×	12 0.3×	21 0.7×	8	245
Mengyang Pu China	7	198 0.6×	51 0.3×	24 0.3×	10 0.3×	45 1.5×	13	287
Ehsan Nezhadarya Canada	8	238 0.8×	66 0.4×	23 0.3×	30 0.8×	10 0.3×	19	324

Countries citing papers authored by Xiaoyang Lyu

Since Specialization

Citations

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

Fields of papers citing papers by Xiaoyang Lyu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaoyang Lyu

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaoyang Lyu. A scholar is included among the top collaborators of Xiaoyang Lyu 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 Xiaoyang Lyu. Xiaoyang Lyu 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:

12 of 12 papers shown

1.

Lyu, Xiaoyang, et al.. (2025). Deformable Radial Kernel Splatting. 21513–21523.

2.

Lyu, Xiaoyang, et al.. (2024). Total-Decom: Decomposed 3D Scene Reconstruction with Minimal Interaction. 20860–20869.

3.

Huang, Yihua, et al.. (2024). SC-GS: Sparse-Controlled Gaussian Splatting for Editable Dynamic Scenes. 4220–4230. 34 indexed citations

4.

Kong, Xin, et al.. (2024). EscherNet: A Generative Model for Scalable View Synthesis. 9503–9513. 5 indexed citations

5.

Lyu, Xiaoyang, et al.. (2023). RICO: Regularizing the Unobservable for Indoor Compositional Reconstruction. 4 indexed citations

6.

Lyu, Xiaoyang, et al.. (2023). Efficient Implicit Neural Reconstruction Using LiDAR. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 8407–8414. 11 indexed citations

7.

Lyu, Xiaoyang, et al.. (2023). Learning A Room with the Occ-SDF Hybrid: Signed Distance Function Mingled with Occupancy Aids Scene Representation. 8906–8916. 8 indexed citations

8.

Hu, Pengfei, Yang Wu, Xiaoyang Lyu, et al.. (2023). Speech2Lip: High-fidelity Speech to Lip Generation by Learning from a Short Video. 22111–22120. 4 indexed citations

9.

Liu, Lina, Xibin Song, Jiadai Sun, et al.. (2023). MFF-Net: Towards Efficient Monocular Depth Completion With Multi-Modal Feature Fusion. IEEE Robotics and Automation Letters. 8(2). 920–927. 24 indexed citations

10.

Zhang, Yinda, et al.. (2023). Hybrid Neural Rendering for Large-Scale Scenes with Motion Blur. 154–164. 8 indexed citations

11.

Lyu, Xiaoyang, Liang Liu, Mengmeng Wang, et al.. (2021). HR-Depth: High Resolution Self-Supervised Monocular Depth Estimation. Proceedings of the AAAI Conference on Artificial Intelligence. 35(3). 2294–2301. 173 indexed citations

12.

Liu, Lina, Xibin Song, Xiaoyang Lyu, et al.. (2021). FCFR-Net: Feature Fusion based Coarse-to-Fine Residual Learning for Depth Completion. Proceedings of the AAAI Conference on Artificial Intelligence. 35(3). 2136–2144. 83 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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