Qi Dai

3.2k total citations · 1 hit paper
39 papers, 1.6k citations indexed

About

Qi Dai is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Qi Dai has authored 39 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Computer Vision and Pattern Recognition, 14 papers in Artificial Intelligence and 2 papers in Signal Processing. Recurrent topics in Qi Dai's work include Human Pose and Action Recognition (12 papers), Video Surveillance and Tracking Methods (12 papers) and Advanced Image and Video Retrieval Techniques (11 papers). Qi Dai is often cited by papers focused on Human Pose and Action Recognition (12 papers), Video Surveillance and Tracking Methods (12 papers) and Advanced Image and Video Retrieval Techniques (11 papers). Qi Dai collaborates with scholars based in China, United States and United Kingdom. Qi Dai's co-authors include Han Hu, Yutong Lin, Yue Cao, Zhenda Xie, Jianmin Bao, Zhuliang Yao, Zheng Zhang, Yu–Gang Jiang, Zhi-Qi Cheng and Xiao Wu and has published in prestigious journals such as Bioinformatics, IEEE Transactions on Image Processing and ACM Computing Surveys.

In The Last Decade

Qi Dai

37 papers receiving 1.5k 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.

SimMIM: a Simple Framework for Masked Image Modeling

2022 715 citations Jianmin Bao, Qi Dai et al. profile →

Peers

Qi Dai

CVPR

AI

MT

BE

RNMI

Quan Zhou China

Ezequiel López‐Rubio Spain

Xiaoheng Jiang China

Ruonan Li China

Suha Kwak South Korea

Junqing Yu China

Quanfu Fan United States

Raghuraman Gopalan United States

Baochen Sun United States

Yuwei Wu China

Quan Zhou China

Qi Dai

1.1k ×0.9

CVPR

537 ×0.8

AI

174 ×1.2

MT

92 ×1.0

BE

144 ×1.6

RNMI

Citations per year, relative to Qi Dai Qi Dai (= 1×) peers Quan Zhou

Countries citing papers authored by Qi Dai

Since Specialization

Citations

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

Fields of papers citing papers by Qi Dai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qi Dai

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

Yu, Xinxin, et al.. (2025). Integrating prior knowledge with deep learning for optimized quality control in corneal images: A multicenter study. Computer Methods and Programs in Biomedicine. 267. 108814–108814. 1 indexed citations

2.

Hu, Keqiang, Jianguo Wei, Changming Sun, et al.. (2025). Synergizing multimodal data and fingerprint space exploration for mechanism of action prediction. Bioinformatics. 41(6).

3.

Xing, Zhen, Xintong Han, Zhi-Qi Cheng, et al.. (2025). StableAnimator: High-Quality Identity-Preserving Human Image Animation. 21096–21106. 1 indexed citations

4.

Huang, Guohua, et al.. (2025). ACP‐DPE: A Dual‐Channel Deep Learning Model for Anticancer Peptide Prediction. IET Systems Biology. 19(1). e70010–e70010. 1 indexed citations

5.

Dai, Qi, et al.. (2024). A Survey on Video Diffusion Models. ACM Computing Surveys. 57(2). 1–42. 41 indexed citations

6.

Dai, Qi, Zhi-Qi Cheng, Han Hu, et al.. (2024). MotionEditor: Editing Video Motion via Content-Aware Diffusion. 7882–7891. 9 indexed citations

7.

Wu, Zuxuan, et al.. (2024). The Role of ViT Design and Training in Robustness to Common Corruptions. IEEE Transactions on Multimedia. 27. 1374–1385.

8.

Feng, Ruoyu, Yanhui Wang, Qi Dai, et al.. (2024). ART•V: Auto-Regressive Text-to-Video Generation with Diffusion Models. 7395–7405. 4 indexed citations

9.

Dai, Qi, et al.. (2024). SimDA: Simple Diffusion Adapter for Efficient Video Generation. 7827–7839. 19 indexed citations

10.

Yan, Xudong, et al.. (2024). BlockGCN: Redefine Topology Awareness for Skeleton-Based Action Recognition. 2049–2058. 33 indexed citations

11.

Liu, Yan, Xiaokang Chen, & Qi Dai. (2023). Parallel Sentence-Level Explanation Generation for Real-World Low-Resource Scenarios. 29. 1–5. 1 indexed citations

12.

Cheng, Zhi-Qi, Qi Dai, & Alexander G. Hauptmann. (2023). ChartReader: A Unified Framework for Chart Derendering and Comprehension without Heuristic Rules. 22145–22156. 3 indexed citations

13.

Liu, Yan, et al.. (2022). MPII: Multi-Level Mutual Promotion for Inference and Interpretation. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 7074–7084. 2 indexed citations

14.

He, Qi, Qi Dai, Xiao Wu, & Jun-Yan He. (2021). A novel class restriction loss for unsupervised domain adaptation. Neurocomputing. 461. 254–265. 3 indexed citations

15.

Cheng, Zhi-Qi, Jun-Xiu Li, Qi Dai, et al.. (2019). Improving the Learning of Multi-column Convolutional Neural Network for Crowd Counting. 1897–1906. 67 indexed citations

16.

Wu, Dayan, Qi Dai, Jing Liu, Bo Li, & Weiping Wang. (2019). Deep Incremental Hashing Network for Efficient Image Retrieval. 9061–9069. 73 indexed citations

17.

Dai, Qi, et al.. (2015). Fudan-Huawei at MediaEval 2015: Detecting Violent Scenes and Affective Impact in Movies with Deep Learning. MediaEval. 43 indexed citations

18.

Dai, Qi, Zuxuan Wu, Yu–Gang Jiang, Xiangyang Xue, & Jinhui Tang. (2014). Fudan-NJUST at MediaEval 2014: Violent Scenes Detection Using Deep Neural Networks.. MediaEval. 15 indexed citations

19.

Dai, Qi, et al.. (2013). Fudan at MediaEval 2013: Violent Scenes Detection Using Motion Features and Part-Level Attributes.. MediaEval. 11 indexed citations

20.

Jiang, Yu–Gang, Qi Dai, Jun Wang, et al.. (2012). Fast Semantic Diffusion for Large-Scale Context-Based Image and Video Annotation. IEEE Transactions on Image Processing. 21(6). 3080–3091. 34 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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