Xiaoyi Dong

3.0k total citations · 2 hit papers
26 papers, 1.6k citations indexed

About

Xiaoyi Dong is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Xiaoyi Dong has authored 26 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Computer Vision and Pattern Recognition, 8 papers in Artificial Intelligence and 3 papers in Signal Processing. Recurrent topics in Xiaoyi Dong's work include Adversarial Robustness in Machine Learning (8 papers), Anomaly Detection Techniques and Applications (4 papers) and Generative Adversarial Networks and Image Synthesis (3 papers). Xiaoyi Dong is often cited by papers focused on Adversarial Robustness in Machine Learning (8 papers), Anomaly Detection Techniques and Applications (4 papers) and Generative Adversarial Networks and Image Synthesis (3 papers). Xiaoyi Dong collaborates with scholars based in China, Hong Kong and United States. Xiaoyi Dong's co-authors include Dongdong Chen, Weiming Zhang, Nenghai Yu, Jianmin Bao, Baining Guo, Dong Chen, Lu Yuan, Xiyang Dai, Zicheng Liu and Yinpeng Chen and has published in prestigious journals such as IEEE Transactions on Image Processing, Neurocomputing and IEEE Transactions on Circuits and Systems for Video Technology.

In The Last Decade

Xiaoyi Dong

21 papers receiving 1.6k citations

Hit Papers

CSWin Transformer: A Gene... 2022 2026 2023 2024 2022 2022 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiaoyi Dong China 11 1.0k 504 252 161 136 26 1.6k
Zihang Jiang China 11 1.2k 1.2× 570 1.1× 263 1.0× 194 1.2× 132 1.0× 23 1.9k
Quan Zhou China 22 1.1k 1.1× 537 1.1× 174 0.7× 148 0.9× 144 1.1× 102 1.7k
Xuran Pan China 11 989 1.0× 331 0.7× 313 1.2× 128 0.8× 256 1.9× 16 1.7k
Mengchen Liu United Kingdom 6 1.3k 1.3× 438 0.9× 301 1.2× 152 0.9× 220 1.6× 7 1.9k
Chun-Fu Richard Chen United States 6 797 0.8× 395 0.8× 199 0.8× 107 0.7× 104 0.8× 12 1.4k
Qiang Wang China 20 1.6k 1.5× 328 0.7× 218 0.9× 245 1.5× 339 2.5× 162 2.3k
Guangwei Gao China 24 1.6k 1.6× 448 0.9× 500 2.0× 68 0.4× 80 0.6× 98 2.1k
Yehui Tang China 15 862 0.8× 491 1.0× 199 0.8× 155 1.0× 101 0.7× 19 1.4k
Hao Gao China 18 613 0.6× 503 1.0× 153 0.6× 135 0.8× 108 0.8× 116 1.4k
Junshi Huang China 14 1.5k 1.5× 729 1.4× 169 0.7× 66 0.4× 82 0.6× 25 2.0k

Countries citing papers authored by Xiaoyi Dong

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoyi Dong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaoyi Dong

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaoyi Dong. A scholar is included among the top collaborators of Xiaoyi Dong 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 Xiaoyi Dong. Xiaoyi Dong 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.
Liu, Ziyu, et al.. (2026). RAR: Retrieving and Ranking Augmented MLLMs for Visual Recognition. IEEE Transactions on Image Processing. 35. 388–401.
2.
Zhang, Pan, Tong Wu, Xiaoyi Dong, et al.. (2025). ByTheWay: Boost Your Text-to-Video Generation Model to Higher Quality in a Training-free Way. 12999–13008. 1 indexed citations
3.
Dong, Xiaoyi, Haodong Duan, Rui Qian, et al.. (2025). OVO-Bench: How Far is Your Video-LLMs from Real-World Online Video Understanding?. 18902–18913.
4.
Hu, Hezhen, Xiaoyi Dong, Jianmin Bao, et al.. (2024). PersonMAE: Person Re-Identification Pre-Training With Masked AutoEncoders. IEEE Transactions on Multimedia. 26. 10029–10040. 5 indexed citations
5.
Duan, Haodong, Lin Chen, Xiaoyi Dong, et al.. (2024). VLMEvalKit: An Open-Source ToolKit for Evaluating Large Multi-Modality Models. 11198–11201. 13 indexed citations
6.
Huang, Qidong, Xiaoyi Dong, Dongdong Chen, et al.. (2024). PointCAT: Contrastive Adversarial Training for Robust Point Cloud Recognition. IEEE Transactions on Image Processing. 33. 2183–2196. 9 indexed citations
7.
Song, W. Y., Kaiwen Zhang, Xiaoyi Dong, et al.. (2024). Long-wavelength near-infrared emission in chromium-activated LiZnNbO4 spinel crystals and valence-converting enhancement via Er3+ ion heterotopic doping. Inorganic Chemistry Frontiers. 11(19). 6536–6548. 3 indexed citations
8.
Dong, Xiaoyi, et al.. (2024). Streaming Long Video Understanding with Large Language Models. 119336–119360.
9.
Chen, Zehui, Xiaoyi Dong, Haodong Duan, et al.. (2024). Are We on the Right Way for Evaluating Large Vision-Language Models?. 27056–27087. 3 indexed citations
10.
Chen, Zehui, Xiaoyi Dong, Haodong Duan, et al.. (2024). ShareGPT4Video: Improving Video Understanding and Generation with Better Captions. 19472–19495. 4 indexed citations
11.
Huang, Qidong, Xiaoyi Dong, Dongdong Chen, et al.. (2023). Improving Adversarial Robustness of Masked Autoencoders via Test-time Frequency-domain Prompting. 1600–1610. 4 indexed citations
12.
Chen, Yuefeng, Kejiang Chen, Xiaoyi Dong, et al.. (2022). Feature Fusion Based Adversarial Example Detection Against Second-Round Adversarial Attacks. IEEE Transactions on Artificial Intelligence. 4(5). 1029–1040. 6 indexed citations
13.
Chen, Yinpeng, Xiyang Dai, Dongdong Chen, et al.. (2022). Mobile-Former: Bridging MobileNet and Transformer. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 5260–5269. 411 indexed citations breakdown →
14.
Dong, Xiaoyi, Jianmin Bao, Dongdong Chen, et al.. (2022). CSWin Transformer: A General Vision Transformer Backbone with Cross-Shaped Windows. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 12114–12124. 824 indexed citations breakdown →
15.
Zhang, Weiming, et al.. (2021). Adversarial steganography based on sparse cover enhancement. Journal of Visual Communication and Image Representation. 80. 103325–103325. 22 indexed citations
16.
Ma, Zehua, et al.. (2021). Local Geometric Distortions Resilient Watermarking Scheme Based on Symmetry. IEEE Transactions on Circuits and Systems for Video Technology. 31(12). 4826–4839. 56 indexed citations
17.
Chen, Dongdong, Kui Zhang, Hang Zhou, et al.. (2021). Adversarial defense via self-orthogonal randomization super-network. Neurocomputing. 452. 147–158. 6 indexed citations
18.
Dong, Xiaoyi, Dongdong Chen, Hang Zhou, et al.. (2020). Self-Robust 3D Point Recognition via Gather-Vector Guidance. 11513–11521. 38 indexed citations
19.
Dong, Xiaoyi, Dongdong Chen, Zehua Ma, et al.. (2020). Robust Superpixel-Guided Attentional Adversarial Attack. 12892–12901. 48 indexed citations
20.
Dong, Xiaoyi, Ruimao Zhang, Dongdong Chen, et al.. (2019). Once a MAN: Towards Multi-Target Attack via Learning Multi-Target Adversarial Network Once. 5157–5166. 20 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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