Leigang Qu

511 total citations
11 papers, 308 citations indexed

About

Leigang Qu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Molecular Biology. According to data from OpenAlex, Leigang Qu has authored 11 papers receiving a total of 308 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Vision and Pattern Recognition, 5 papers in Artificial Intelligence and 1 paper in Molecular Biology. Recurrent topics in Leigang Qu's work include Multimodal Machine Learning Applications (6 papers), Advanced Image and Video Retrieval Techniques (5 papers) and Video Analysis and Summarization (4 papers). Leigang Qu is often cited by papers focused on Multimodal Machine Learning Applications (6 papers), Advanced Image and Video Retrieval Techniques (5 papers) and Video Analysis and Summarization (4 papers). Leigang Qu collaborates with scholars based in China, Singapore and Hong Kong. Leigang Qu's co-authors include Liqiang Nie, Meng Liu, Zan Gao, Qi Tian, Jianlong Wu, Da Cao, Tat‐Seng Chua, Hao Fei, Shengqiong Wu and Min Zhang and has published in prestigious journals such as arXiv (Cornell University) and Proceedings of the 30th ACM International Conference on Multimedia.

In The Last Decade

Leigang Qu

9 papers receiving 305 citations

Peers

Leigang Qu

CVPR

AI

IS

SP

MT

Jiabo Ye China

Weichong Yin China

Difei Gao Singapore

Ladislav Lenc Czechia

Rakshith Shetty Germany

Luca Piras Italy

Sai Rajeswar India

Weiwei Sun China

Vladimir Pervouchine Singapore

Jiabo Ye China

Leigang Qu

192 ×0.8

CVPR

163 ×1.1

AI

18 ×0.9

IS

5 ×0.3

SP

14 ×0.9

MT

Citations per year, relative to Leigang Qu Leigang Qu (= 1×) peers Jiabo Ye

Countries citing papers authored by Leigang Qu

Since Specialization

Citations

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

Fields of papers citing papers by Leigang Qu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Leigang Qu

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

11 of 11 papers shown

1.

Qu, Leigang, et al.. (2025). SILMM: Self-Improving Large Multimodal Models for Compositional Text-to-Image Generation. 18497–18508.

2.

Li, Yongqi, Wenjie Wang, Leigang Qu, et al.. (2025). Revolutionizing Text-to-Image Retrieval as Autoregressive Token-to-Voken Generation. 813–822. 1 indexed citations

3.

Li, Yongqi, Wenjie Wang, Leigang Qu, et al.. (2024). Generative Cross-Modal Retrieval: Memorizing Images in Multimodal Language Models for Retrieval and Beyond. 11851–11861. 6 indexed citations

4.

Nguyen, Thông, Bin Yi, Junbin Xiao, et al.. (2024). Video-Language Understanding: A Survey from Model Architecture, Model Training, and Data Perspectives. 3636–3657.

5.

Qu, Leigang, Wenjie Wang, Yongqi Li, et al.. (2024). Discriminative Probing and Tuning for Text-to-Image Generation. 7434–7444. 2 indexed citations

6.

Wang, Wenjie, et al.. (2023). Popularity-aware Distributionally Robust Optimization for Recommendation System. 4967–4973. 8 indexed citations

7.

Qu, Leigang, Meng Liu, Wenjie Wang, et al.. (2023). Learnable Pillar-based Re-ranking for Image-Text Retrieval. arXiv (Cornell University). 1252–1261. 9 indexed citations

8.

Qu, Leigang, Shengqiong Wu, Hao Fei, Liqiang Nie, & Tat‐Seng Chua. (2023). LayoutLLM-T2I: Eliciting Layout Guidance from LLM for Text-to-Image Generation. 643–654. 35 indexed citations

9.

Nie, Liqiang, Leigang Qu, Meng Dai, et al.. (2022). Search-oriented Micro-video Captioning. Proceedings of the 30th ACM International Conference on Multimedia. 3234–3243. 24 indexed citations

10.

Qu, Leigang, Meng Liu, Jianlong Wu, Zan Gao, & Liqiang Nie. (2021). Dynamic Modality Interaction Modeling for Image-Text Retrieval. 1104–1113. 121 indexed citations

11.

Qu, Leigang, Meng Liu, Da Cao, Liqiang Nie, & Qi Tian. (2020). Context-Aware Multi-View Summarization Network for Image-Text Matching. 1047–1055. 102 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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