Leida Li

7.3k total citations · 1 hit paper
241 papers, 5.1k citations indexed

About

Leida Li is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Leida Li has authored 241 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 225 papers in Computer Vision and Pattern Recognition, 76 papers in Media Technology and 24 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Leida Li's work include Image and Video Quality Assessment (134 papers), Advanced Image Processing Techniques (68 papers) and Visual Attention and Saliency Detection (67 papers). Leida Li is often cited by papers focused on Image and Video Quality Assessment (134 papers), Advanced Image Processing Techniques (68 papers) and Visual Attention and Saliency Detection (67 papers). Leida Li collaborates with scholars based in China, Singapore and United States. Leida Li's co-authors include Jinjian Wu, Weisi Lin, Guangming Shi, Weisheng Dong, Hancheng Zhu, Yuming Fang, Gaobo Yang, Ke Gu, Jiansheng Qian and Jeng‐Shyang Pan and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Industrial Electronics.

In The Last Decade

Leida Li

224 papers receiving 5.0k citations

Hit Papers

MetaIQA: Deep Meta-Learning for No-Reference Image Qualit... 2020 2026 2022 2024 2020 50 100 150 200 250
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.

  1. MetaIQA: Deep Meta-Learning for No-Reference Image Quality Assessment
    2020 254 citations Hancheng Zhu, Leida Li et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Leida Li China 38 4.5k 1.9k 329 326 249 241 5.1k
Jinjian Wu China 32 3.5k 0.8× 2.1k 1.1× 203 0.6× 188 0.6× 255 1.0× 169 4.2k
Yuming Fang China 45 6.9k 1.5× 2.7k 1.4× 383 1.2× 512 1.6× 329 1.3× 272 7.6k
Doron Tal United States 5 4.5k 1.0× 2.1k 1.1× 224 0.7× 496 1.5× 91 0.4× 13 5.2k
Jan‐Mark Geusebroek Netherlands 27 3.1k 0.7× 764 0.4× 243 0.7× 736 2.3× 359 1.4× 83 4.1k
Aseem Agarwala United States 35 5.2k 1.2× 1.4k 0.8× 214 0.7× 186 0.6× 228 0.9× 63 5.8k
S.S. Hemami United States 27 5.5k 1.2× 1.2k 0.7× 582 1.8× 189 0.6× 260 1.0× 126 5.9k
Lina J. Karam United States 30 2.7k 0.6× 1.0k 0.5× 154 0.5× 255 0.8× 140 0.6× 193 3.8k
Anush K. Moorthy United States 21 7.5k 1.7× 3.8k 2.1× 286 0.9× 166 0.5× 596 2.4× 38 8.1k
Damon M. Chandler United States 27 4.3k 1.0× 2.1k 1.1× 349 1.1× 78 0.2× 543 2.2× 87 4.7k
Rajiv Soundararajan India 14 5.8k 1.3× 2.5k 1.3× 114 0.3× 124 0.4× 314 1.3× 49 6.3k

Countries citing papers authored by Leida Li

Since Specialization
Citations

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

Fields of papers citing papers by Leida Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Leida Li

This figure shows the co-authorship network connecting the top 25 collaborators of Leida Li. A scholar is included among the top collaborators of Leida 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 Leida Li. Leida 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.
Zhang, Mingyang, et al.. (2025). Diffusion Model-Based Visual Compensation Guidance and Visual Difference Analysis for No-Reference Image Quality Assessment. IEEE Transactions on Image Processing. 34. 263–278. 1 indexed citations
2.
Tang, Lu, et al.. (2025). GAN-Guided Few-Shot Attention Network for Medical Images Fusion Quality Assessment. IEEE Transactions on Medical Imaging. 44(11). 4292–4306. 1 indexed citations
3.
Jia, Zheng, et al.. (2024). Blind image quality index with high-level Semantic Guidance and low-level fine-grained Representation. Neurocomputing. 600. 128151–128151.
4.
Li, Leida, et al.. (2024). Emotion-aware hierarchical interaction network for multimodal image aesthetics assessment. Pattern Recognition. 154. 110584–110584. 6 indexed citations
5.
Chen, Pengfei, et al.. (2024). AesExpert: Towards Multi-modality Foundation Model for Image Aesthetics Perception. 5911–5920. 6 indexed citations
6.
Yang, Wen, et al.. (2024). Learning Frame-Event Fusion for Motion Deblurring. IEEE Transactions on Image Processing. 33. 6836–6849. 2 indexed citations
7.
Zhu, Hancheng, Zhiwen Shao, Rui Yao, et al.. (2024). Attribute-Driven Multimodal Hierarchical Prompts for Image Aesthetic Quality Assessment. 2399–2408.
8.
Wu, Jinjian, et al.. (2023). Transfer learning for just noticeable difference estimation. Information Sciences. 648. 119575–119575. 2 indexed citations
9.
Zhu, Hancheng, Zhiwen Shao, Yong Zhou, et al.. (2023). Personalized Image Aesthetics Assessment with Attribute-guided Fine-grained Feature Representation. 6794–6802. 7 indexed citations
10.
Li, Leida, Pengfei Chen, Jinjian Wu, et al.. (2023). AesCLIP: Multi-Attribute Contrastive Learning for Image Aesthetics Assessment. 1117–1126. 11 indexed citations
11.
Li, Leida, et al.. (2023). Blind Image Quality Index With Cross-Domain Interaction and Cross-Scale Integration. IEEE Transactions on Multimedia. 26. 2729–2739. 7 indexed citations
12.
Zhou, Yu, et al.. (2023). Quality Assessment for Stitched Panoramic Images via Patch Registration and Bidimensional Feature Aggregation. IEEE Transactions on Multimedia. 26. 3354–3365. 7 indexed citations
13.
Chen, Pengfei, Leida Li, Haoliang Li, et al.. (2022). Dynamic Expert-Knowledge Ensemble for Generalizable Video Quality Assessment. IEEE Transactions on Circuits and Systems for Video Technology. 33(6). 2577–2589. 6 indexed citations
14.
Guo, Pengfei, Hantao Liu, Delu Zeng, et al.. (2022). An Underwater Image Quality Assessment Metric. IEEE Transactions on Multimedia. 25. 5093–5106. 23 indexed citations
15.
Huang, Tao, Weisheng Dong, Jinjian Wu, et al.. (2022). Deep Hyperspectral Image Fusion Network With Iterative Spatio-Spectral Regularization. IEEE Transactions on Computational Imaging. 8. 201–214. 59 indexed citations
16.
Yang, Xiaohan, Fan Li, Leida Li, Ke Gu, & Hantao Liu. (2022). Study of Natural Scene Categories in Measurement of Perceived Image Quality. IEEE Transactions on Instrumentation and Measurement. 71. 1–12. 7 indexed citations
17.
Liu, Yongxu, Jinjian Wu, Leida Li, et al.. (2021). Video Quality Assessment With Serial Dependence Modeling. IEEE Transactions on Multimedia. 24. 3754–3768. 7 indexed citations
18.
Wang, Miaohui, Yi‐Jing Huang, Wuyuan Xie, et al.. (2021). Quality Measurement of Screen Images via Foreground Perception and Background Suppression. IEEE Transactions on Instrumentation and Measurement. 70. 1–11. 6 indexed citations
19.
Zhou, Yu, Leida Li, Shiqi Wang, et al.. (2019). No-Reference Quality Assessment for View Synthesis Using DoG-Based Edge Statistics and Texture Naturalness. IEEE Transactions on Image Processing. 28(9). 4566–4579. 57 indexed citations
20.
Wu, Jinjian, Leida Li, Weisheng Dong, et al.. (2017). Enhanced Just Noticeable Difference Model for Images With Pattern Complexity. IEEE Transactions on Image Processing. 26(6). 2682–2693. 120 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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