Tao Dai

3.6k total citations · 1 hit paper
91 papers, 1.9k citations indexed

About

Tao Dai is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Tao Dai has authored 91 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Computer Vision and Pattern Recognition, 27 papers in Artificial Intelligence and 27 papers in Media Technology. Recurrent topics in Tao Dai's work include Advanced Image Processing Techniques (25 papers), Image and Signal Denoising Methods (17 papers) and Image Processing Techniques and Applications (16 papers). Tao Dai is often cited by papers focused on Advanced Image Processing Techniques (25 papers), Image and Signal Denoising Methods (17 papers) and Image Processing Techniques and Applications (16 papers). Tao Dai collaborates with scholars based in China, United States and Hong Kong. Tao Dai's co-authors include Shu‐Tao Xia, Yongbing Zhang, Jianrui Cai, Lei Zhang, Yong Jiang, Bin Chen, Weizhi Lu, Jian Lü, Feng Yan and Yan Feng and has published in prestigious journals such as Energy & Environmental Science, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

Tao Dai

82 papers receiving 1.9k 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.

Second-Order Attention Network for Single Image Super-Resolution

2019 1.2k citations Tao Dai, Shu‐Tao Xia et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tao Dai China	17	1.5k	913	304	97	91	91	1.9k
Rui Song China	24	992 0.6×	906 1.0×	281 0.9×	68 0.7×	51 0.6×	95	1.7k
Abhishek Singh India	12	2.3k 1.5×	1.5k 1.6×	175 0.6×	148 1.5×	206 2.3×	66	2.8k
Michaël Gharbi United States	17	1.3k 0.8×	381 0.4×	695 2.3×	53 0.5×	165 1.8×	30	2.2k
F. Russo Italy	24	1.3k 0.8×	722 0.8×	324 1.1×	242 2.5×	119 1.3×	90	1.9k
Vassilios Chatzis Greece	8	794 0.5×	493 0.5×	248 0.8×	91 0.9×	48 0.5×	29	1.2k
Moon Gi Kang South Korea	19	1.0k 0.7×	602 0.7×	88 0.3×	101 1.0×	98 1.1×	127	1.4k
Xiaoyan Sun China	25	2.5k 1.6×	756 0.8×	275 0.9×	407 4.2×	122 1.3×	132	2.8k
Wei‐Sheng Lai United States	19	2.1k 1.4×	967 1.1×	62 0.2×	100 1.0×	126 1.4×	27	2.4k
Jin Zheng China	15	1.6k 1.0×	733 0.8×	188 0.6×	41 0.4×	34 0.4×	62	2.0k
Sumohana S. Channappayya India	17	1.3k 0.9×	616 0.7×	71 0.2×	129 1.3×	53 0.6×	91	1.7k

Countries citing papers authored by Tao Dai

Since Specialization

Citations

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

Fields of papers citing papers by Tao Dai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tao Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Tao Dai. A scholar is included among the top collaborators of Tao Dai 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 Tao Dai. Tao Dai 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.

Yang, Zhengduo, et al.. (2025). MAGAE: Multi-Level Alignment Over Aggregation Semantic Graph With Attribute Enhancement for Text-Based Vehicle Retrieval. IEEE Transactions on Intelligent Transportation Systems. 26(9). 13704–13720.

2.

Gao, Can, et al.. (2025). MC3D-AD: A Unified Geometry-aware Reconstruction Model for Multi-category 3D Anomaly Detection. arXiv (Cornell University). 837–845.

3.

Dai, Tao, et al.. (2025). Creep life prediction of 10CrMo910 steel main steam pipes based on carbide evolution and machine learning. Materials Today Communications. 45. 112378–112378. 1 indexed citations

4.

Zha, Yan, et al.. (2025). MambaIRv2: Attentive State Space Restoration. 28124–28133. 13 indexed citations

5.

Wang, Yanzi, Hang Guo, Jinpeng Wang, et al.. (2025). PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter. 16976–16986.

6.

Dai, Tao, et al.. (2024). IterMeme: Expert-Guided Multimodal LLM for Interactive Meme Creation with Layout-Aware Generation. 720–728. 9 indexed citations

7.

Wang, Jinpeng, et al.. (2024). Pyramid hybrid pooling quantization for efficient fine-grained image retrieval. Pattern Recognition Letters. 178. 106–114. 6 indexed citations

8.

Lu, Longfei, et al.. (2024). Large Point-to-Gaussian Model for Image-to-3D Generation. 10843–10852. 2 indexed citations

9.

Wu, Yong, Nan Wang, Tao Dai, & Dong Cheng. (2024). Information security outsourcing strategies in the supply chain considering security externality. Journal of the Operational Research Society. 76(3). 482–497.

10.

Dai, Tao, et al.. (2024). CluSAD: Self-Supervised Learning-Based Anomaly Detection for Industrial Control Systems. 545–552. 1 indexed citations

11.

Zhou, Yimin, et al.. (2024). Progressive Learning with Visual Prompt Tuning for Variable-Rate Image Compression. 1767–1773. 1 indexed citations

12.

Dai, Tao, et al.. (2023). One-stage Low-resolution Text Recognition with High-resolution Knowledge Transfer. 2189–2198. 2 indexed citations

13.

Zhao, Bowen, et al.. (2023). Toward Effective Image Manipulation Detection With Proposal Contrastive Learning. IEEE Transactions on Circuits and Systems for Video Technology. 33(9). 4703–4714. 24 indexed citations

14.

Dai, Tao, et al.. (2023). CFGN: A Lightweight Context Feature Guided Network for Image Super-Resolution. IEEE Transactions on Emerging Topics in Computational Intelligence. 8(1). 855–865. 10 indexed citations

15.

Dai, Tao & Yanjie Li. (2023). Efficient dual domain image denoising via SURE-based optimization. International Journal of Machine Learning and Cybernetics. 14(12). 4417–4430. 1 indexed citations

16.

Huang, Yujun, et al.. (2023). Learned Distributed Image Compression with Multi-Scale Patch Matching in Feature Domain. Proceedings of the AAAI Conference on Artificial Intelligence. 37(4). 4322–4329. 2 indexed citations

17.

Li, Jinmin, et al.. (2023). FSR: A General Frequency-Oriented Framework to Accelerate Image Super-resolution Networks. Proceedings of the AAAI Conference on Artificial Intelligence. 37(1). 1343–1350. 5 indexed citations

18.

Chen, Bin, Feng Yan, Tao Dai, et al.. (2022). Adversarial Examples Generation for Deep Product Quantization Networks on Image Retrieval. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(2). 1388–1404. 20 indexed citations

19.

Dai, Tao, et al.. (2021). HiddenTag: Enabling Person Identification Without Privacy Exposure. ZTE communications. 19(3). 3–12.

20.

Bai, Yang, Yan Feng, Yisen Wang, et al.. (2019). Hilbert-Based Generative Defense for Adversarial Examples. 4783–4792. 29 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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