Hongyang Li

3.3k total citations
25 papers, 1.0k citations indexed

About

Hongyang Li is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Aerospace Engineering. According to data from OpenAlex, Hongyang Li has authored 25 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Computer Vision and Pattern Recognition, 11 papers in Artificial Intelligence and 4 papers in Aerospace Engineering. Recurrent topics in Hongyang Li's work include Advanced Neural Network Applications (17 papers), Domain Adaptation and Few-Shot Learning (9 papers) and Advanced Image and Video Retrieval Techniques (8 papers). Hongyang Li is often cited by papers focused on Advanced Neural Network Applications (17 papers), Domain Adaptation and Few-Shot Learning (9 papers) and Advanced Image and Video Retrieval Techniques (8 papers). Hongyang Li collaborates with scholars based in China, Hong Kong and Australia. Hongyang Li's co-authors include Xiaogang Wang, Huchuan Lu, David Eigen, Samuel Dodge, Matthew D. Zeiler, Xiaohui Shen, Zhe Lin, Brian Price, Wanli Ouyang and Junjie Yan and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Image Processing.

In The Last Decade

Hongyang Li

22 papers receiving 997 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hongyang Li China 14 806 374 126 90 82 25 1.0k
Keze Wang China 16 874 1.1× 543 1.5× 42 0.3× 110 1.2× 63 0.8× 38 1.3k
Thanh-Toan Do Australia 19 608 0.8× 244 0.7× 163 1.3× 65 0.7× 24 0.3× 52 895
Yu-Huan Wu China 10 609 0.8× 190 0.5× 80 0.6× 134 1.5× 27 0.3× 13 822
Chi Su China 16 1.7k 2.1× 536 1.4× 56 0.4× 94 1.0× 30 0.4× 43 2.0k
Jae-Yeal Nam South Korea 20 1.0k 1.3× 162 0.4× 86 0.7× 126 1.4× 50 0.6× 56 1.4k
Tianshui Chen China 18 1.4k 1.7× 891 2.4× 45 0.4× 114 1.3× 33 0.4× 59 1.8k
Mei-Chen Yeh Taiwan 12 1.1k 1.4× 230 0.6× 92 0.7× 112 1.2× 20 0.2× 48 1.3k
Seunghoon Hong South Korea 13 967 1.2× 321 0.9× 90 0.7× 71 0.8× 12 0.1× 25 1.2k
Yu Zeng China 11 510 0.6× 156 0.4× 27 0.2× 66 0.7× 46 0.6× 23 740

Countries citing papers authored by Hongyang Li

Since Specialization
Citations

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

Fields of papers citing papers by Hongyang Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hongyang Li

This figure shows the co-authorship network connecting the top 25 collaborators of Hongyang Li. A scholar is included among the top collaborators of Hongyang Li 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 Hongyang Li. Hongyang Li 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.
Yang, Zetong, Li Chen, Yanan Sun, & Hongyang Li. (2024). Visual Point Cloud Forecasting Enables Scalable Autonomous Driving. 14673–14684. 16 indexed citations
2.
3.
Li, Hongyang, et al.. (2024). SCMEA: A stacked co-enhanced model for entity alignment based on multi-aspect information fusion and bidirectional contrastive learning. Neural Networks. 173. 106178–106178. 6 indexed citations
4.
Li, Feng, Ailing Zeng, Shilong Liu, et al.. (2023). Lite DETR : An Interleaved Multi-Scale Encoder for Efficient DETR. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 18558–18567. 61 indexed citations
5.
Li, Hongyang, Hao Zhang, Zhaoyang Zeng, et al.. (2023). DFA3D: 3D Deformable Attention For 2D-to-3D Feature Lifting. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 6661–6670. 9 indexed citations
6.
Gao, Peng, Renrui Zhang, Rongyao Fang, et al.. (2023). Mimic before Reconstruct: Enhancing Masked Autoencoders with Feature Mimicking. International Journal of Computer Vision. 132(5). 1546–1556. 13 indexed citations
7.
Li, Hongyang, et al.. (2022). The design of following controller for autonomous vehicle based on leader-follower strategies. SHILAP Revista de lepidopterología. 355. 3029–3029.
8.
He, Yuan, et al.. (2021). MonoEF: Extrinsic Parameter Free Monocular 3D Object Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence. 44(12). 10114–10128. 19 indexed citations
9.
Yang, Yibo, Shan You, Hongyang Li, et al.. (2021). Towards Improving the Consistency, Efficiency, and Flexibility of Differentiable Neural Architecture Search. 6663–6672. 29 indexed citations
10.
Yang, Yibo, Hongyang Li, Shan You, et al.. (2020). ISTA-NAS: Efficient and Consistent Neural Architecture Search by Sparse Coding.. Neural Information Processing Systems. 33. 10503–10513. 1 indexed citations
11.
Yang, Yibo, Hongyang Li, Xia Li, et al.. (2020). SOGNet: Scene Overlap Graph Network for Panoptic Segmentation. Proceedings of the AAAI Conference on Artificial Intelligence. 34(7). 12637–12644. 34 indexed citations
12.
Li, Hongyang, Bo Dai, Shaoshuai Shi, Wanli Ouyang, & Xiaogang Wang. (2019). Feature Intertwiner for Object Detection.. The HKU Scholars Hub (University of Hong Kong). 6 indexed citations
13.
Li, Hongyang, David Eigen, Samuel Dodge, Matthew D. Zeiler, & Xiaogang Wang. (2019). Finding Task-Relevant Features for Few-Shot Learning by Category Traversal. The HKU Scholars Hub (University of Hong Kong). 1–10. 242 indexed citations
14.
Li, Hongyang, Yu Liu, Wanli Ouyang, & Xiaogang Wang. (2018). Zoom Out-and-In Network with Map Attention Decision for Region Proposal and Object Detection. International Journal of Computer Vision. 127(3). 225–238. 64 indexed citations
15.
Li, Hongyang, et al.. (2017). Do we really need more training data for object localization. The HKU Scholars Hub (University of Hong Kong). 313. 775–779. 4 indexed citations
16.
Liu, Yu, Hongyang Li, Junjie Yan, et al.. (2017). Recurrent Scale Approximation for Object Detection in CNN. The HKU Scholars Hub (University of Hong Kong). 571–579. 63 indexed citations
17.
Li, Hongyang, et al.. (2016). CNN for saliency detection with low-level feature integration. Neurocomputing. 226. 212–220. 71 indexed citations
18.
Ouyang, Wanli, Xingyu Zeng, Xiaogang Wang, et al.. (2016). DeepID-Net: Object Detection with Deformable Part Based Convolutional Neural Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence. 39(7). 1320–1334. 132 indexed citations
19.
Li, Hongyang, Huchuan Lu, Zhe Lin, Xiaohui Shen, & Brian Price. (2015). Inner and Inter Label Propagation: Salient Object Detection in the Wild. IEEE Transactions on Image Processing. 24(10). 3176–3186. 157 indexed citations
20.
Ouyang, Wanli, Hongyang Li, Xingyu Zeng, & Xiaogang Wang. (2015). Learning Deep Representation with Large-Scale Attributes. The HKU Scholars Hub (University of Hong Kong). 1895–1903. 15 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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