Liang-Yan Gui

1.2k total citations · 1 hit paper
20 papers, 394 citations indexed

About

Liang-Yan Gui is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Control and Systems Engineering. According to data from OpenAlex, Liang-Yan Gui has authored 20 papers receiving a total of 394 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computer Vision and Pattern Recognition, 5 papers in Artificial Intelligence and 3 papers in Control and Systems Engineering. Recurrent topics in Liang-Yan Gui's work include Advanced Neural Network Applications (4 papers), Video Surveillance and Tracking Methods (3 papers) and Domain Adaptation and Few-Shot Learning (3 papers). Liang-Yan Gui is often cited by papers focused on Advanced Neural Network Applications (4 papers), Video Surveillance and Tracking Methods (3 papers) and Domain Adaptation and Few-Shot Learning (3 papers). Liang-Yan Gui collaborates with scholars based in United States, China and Jamaica. Liang-Yan Gui's co-authors include Yu-Xiong Wang, José M. F. Moura, Alexander G. Schwing, Sergey Tulyakov, Hsin-Ying Lee, Dhiraj Joshi, Shengcao Cao, Manuela Veloso, Xiaodan Liang and Kevin Zhang and has published in prestigious journals such as NeuroImage, IEEE Control Systems and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

In The Last Decade

Liang-Yan Gui

18 papers receiving 386 citations

Hit Papers

align trajectories

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.

SDFusion: Multimodal 3D Shape Completion, Reconstruction, and Generation

2023 97 citations Hsin-Ying Lee, Sergey Tulyakov et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Liang-Yan Gui United States	9	236	103	80	72	63	20	394
Chun-Hao P. Huang Germany	9	359 1.5×	79 0.8×	106 1.3×	85 1.2×	38 0.6×	26	463
Jiemin Fang China	11	391 1.7×	146 1.4×	80 1.0×	24 0.3×	89 1.4×	20	531
Di Kang China	10	417 1.8×	160 1.6×	97 1.2×	60 0.8×	68 1.1×	22	509
Eunbyung Park South Korea	9	490 2.1×	185 1.8×	83 1.0×	19 0.3×	98 1.6×	20	658
Ilya Kostrikov United States	11	218 0.9×	144 1.4×	54 0.7×	60 0.8×	35 0.6×	15	356
Tanner Schmidt United States	9	382 1.6×	40 0.4×	108 1.4×	126 1.8×	124 2.0×	11	496
M. Zeeshan Zia Germany	13	452 1.9×	96 0.9×	48 0.6×	48 0.7×	11 0.2×	17	549
Yilun Du United States	8	391 1.7×	120 1.2×	245 3.1×	91 1.3×	221 3.5×	18	610
Andrei Zanfir Romania	8	637 2.7×	116 1.1×	210 2.6×	93 1.3×	47 0.7×	11	708
Timur Bagautdinov United States	10	477 2.0×	151 1.5×	199 2.5×	56 0.8×	139 2.2×	19	589

Countries citing papers authored by Liang-Yan Gui

Since Specialization

Citations

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

Fields of papers citing papers by Liang-Yan Gui

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Liang-Yan Gui. 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 Liang-Yan Gui. The network helps show where Liang-Yan Gui may publish in the future.

Co-authorship network of co-authors of Liang-Yan Gui

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

20 of 20 papers shown

1.

Zhang, Jianming, et al.. (2025). Floating No More: Object-Ground Reconstruction from a Single Image. 27134–27143. 1 indexed citations

2.

Ling, Hung Yu, et al.. (2025). InterMimic: Towards Universal Whole-Body Control for Physics-Based Human-Object Interactions. 12266–12277. 1 indexed citations

3.

Sun, Zhiqing, Sheng Shen, Chunyuan Li, et al.. (2024). Aligning Large Multimodal Models with Factually Augmented RLHF. 13088–13110. 29 indexed citations

4.

Gui, Liang-Yan, et al.. (2024). Situational Awareness Matters in 3D Vision Language Reasoning. 13678–13688. 3 indexed citations

5.

Gui, Liang-Yan, et al.. (2024). InterDreamer: Zero-Shot Text to 3D Dynamic Human-Object Interaction. 52858–52890. 1 indexed citations

6.

Lee, Hsin-Ying, et al.. (2023). SDFusion: Multimodal 3D Shape Completion, Reconstruction, and Generation. 4456–4465. 97 indexed citations breakdown →

7.

Cao, Shengcao, Dhiraj Joshi, Liang-Yan Gui, & Yu-Xiong Wang. (2023). Contrastive Mean Teacher for Domain Adaptive Object Detectors. 23839–23848. 60 indexed citations

8.

Gui, Liang-Yan, et al.. (2023). DualCross: Cross-Modality Cross-Domain Adaptation for Monocular BEV Perception. 10910–10917. 3 indexed citations

9.

Li, Zhengyuan, et al.. (2023). InterDiff: Generating 3D Human-Object Interactions with Physics-Informed Diffusion. 14882–14894. 34 indexed citations

10.

Gui, Liang-Yan, et al.. (2023). BEV-Guided Multi-Modality Fusion for Driving Perception. 21960–21969. 28 indexed citations

11.

Luo, Wenjie, et al.. (2022). Joint Forecasting of Panoptic Segmentations with Difference Attention. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 2617–2626. 1 indexed citations

12.

Gui, Liang-Yan, Liangke Gui, Yu-Xiong Wang, Louis–Philippe Morency, & José M. F. Moura. (2018). Factorized Convolutional Networks: Unsupervised Fine-Tuning for Image Clustering. 7 indexed citations

13.

Gui, Liang-Yan, Kevin Zhang, Yu-Xiong Wang, et al.. (2018). Teaching Robots to Predict Human Motion. 562–567. 68 indexed citations

14.

Franchetti, Franz, Tze Meng Low, Stefan Mitsch, et al.. (2017). High-Assurance SPIRAL: End-to-End Guarantees for Robot and Car Control. IEEE Control Systems. 37(2). 82–103. 21 indexed citations

15.

Gui, Liang-Yan, Xiaoying Tang, & José M. F. Moura. (2016). Geodesic distance on a Grassmannian for monitoring the progression of Alzheimer's disease. NeuroImage. 146. 1016–1024. 8 indexed citations

16.

Gui, Liang-Yan, et al.. (2015). Traffic flow from a low frame rate city camera. 3802–3806. 21 indexed citations

17.

Wang, Dajin & Liang-Yan Gui. (2014). Relay Channel with Causal Channel State Information. 1–5.

18.

Wang, Yu-Xiong, Liang-Yan Gui, & Yu‐Jin Zhang. (2012). Neighborhood Preserving Non-negative Tensor Factorization for image representation. 3389–3392. 10 indexed citations

19.

Wang, Dajin & Liang-Yan Gui. (2012). Noisy network coding with causal channel state information. 9. 67–72.

20.

Gui, Liang-Yan, Lin Yuan, Shengjin Wang, & Xiaoqing Ding. (2011). Accurate face segmentation based on fusion of improved GrabCut and ASM. 1175–1179. 1 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.

Explore authors with similar magnitude of impact