Qi Qi

871 total citations · 1 hit paper
15 papers, 600 citations indexed

About

Qi Qi is a scholar working on Computer Vision and Pattern Recognition, Atomic and Molecular Physics, and Optics and Cognitive Neuroscience. According to data from OpenAlex, Qi Qi has authored 15 papers receiving a total of 600 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Vision and Pattern Recognition, 1 paper in Atomic and Molecular Physics, and Optics and 1 paper in Cognitive Neuroscience. Recurrent topics in Qi Qi's work include Image Enhancement Techniques (10 papers), Advanced Image Processing Techniques (7 papers) and Image and Signal Denoising Methods (5 papers). Qi Qi is often cited by papers focused on Image Enhancement Techniques (10 papers), Advanced Image Processing Techniques (7 papers) and Image and Signal Denoising Methods (5 papers). Qi Qi collaborates with scholars based in China, Canada and Hong Kong. Qi Qi's co-authors include Kunqian Li, Dalei Song, Kun Sun, Guojia Hou, Xiang Gao, Haiyong Zheng, Q. M. Jonathan Wu, Xinghao Ding, Xueyang Fu and Zheng-Jun Zha and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Transactions on Image Processing and Industrial & Engineering Chemistry Research.

In The Last Decade

Qi Qi

14 papers receiving 591 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.

SGUIE-Net: Semantic Attention Guided Underwater Image Enhancement With Multi-Scale Perception

2022 159 citations Qi Qi, Kunqian Li et al. IEEE Transactions on Image Processing profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Qi Qi China	10	538	195	44	29	28	15	600
Jieyu Yuan China	10	356 0.7×	144 0.7×	50 1.1×	21 0.7×	30 1.1×	17	458
Minjun Hou China	5	719 1.3×	280 1.4×	60 1.4×	27 0.9×	43 1.5×	6	769
Xin Luan China	7	255 0.5×	107 0.5×	27 0.6×	15 0.5×	31 1.1×	36	311
FABIOLA FIDELIZ GOMES DE MORAES Brazil	2	578 1.1×	259 1.3×	33 0.8×	24 0.8×	38 1.4×	2	598
Huihui Yue China	8	316 0.6×	108 0.6×	27 0.6×	77 2.7×	24 0.9×	20	419
Shenghui Rong China	11	196 0.4×	128 0.7×	11 0.3×	25 0.9×	15 0.5×	36	327
Wan Nural Jawahir Hj Wan Yussof Malaysia	7	340 0.6×	150 0.8×	10 0.2×	29 1.0×	10 0.4×	23	411
Keming Cao United States	6	644 1.2×	288 1.5×	23 0.5×	22 0.8×	31 1.1×	6	710
Ling Mei China	6	272 0.5×	93 0.5×	9 0.2×	17 0.6×	18 0.6×	14	289
Mingye Ju China	12	713 1.3×	451 2.3×	10 0.2×	29 1.0×	11 0.4×	34	772

Countries citing papers authored by Qi Qi

Since Specialization

Citations

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

Fields of papers citing papers by Qi Qi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qi Qi

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

15 of 15 papers shown

Li, Kunqian, et al.. (2025). Underwater image enhancement by diffusion model with customized CLIP-classifier. Pattern Recognition. 171. 112232–112232. 1 indexed citations

Li, Kunqian, Wenjie Liu, Qi Qi, et al.. (2024). Learning Scribbles for Dense Depth: Weakly Supervised Single Underwater Image Depth Estimation Boosted by Multitask Learning. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–15. 12 indexed citations

Zhang, Yongchang, Qi Qi, Kunqian Li, & Dandan Liu. (2023). Underwater video consistent enhancement: a real-world dataset and solution with progressive quality learning. Multimedia Tools and Applications. 83(3). 7335–7361. 3 indexed citations

Li, Kunqian, et al.. (2023). TCTL-Net: Template-Free Color Transfer Learning for Self-Attention Driven Underwater Image Enhancement. IEEE Transactions on Circuits and Systems for Video Technology. 34(6). 4682–4697. 22 indexed citations

Zhao, Sanyuan, et al.. (2023). Learning Fine-Grained Information with Capsule-Wise Attention for Salient Object Detection. IEEE Transactions on Multimedia. 1–14. 5 indexed citations

Qi, Qi, Kunqian Li, Haiyong Zheng, et al.. (2022). SGUIE-Net: Semantic Attention Guided Underwater Image Enhancement With Multi-Scale Perception. IEEE Transactions on Image Processing. 31. 6816–6830. 159 indexed citations breakdown →

Yang, Hua, Fei Tian, Qi Qi, Q. M. Jonathan Wu, & Kunqian Li. (2022). Underwater image enhancement with latent consistency learning‐based color transfer. IET Image Processing. 16(6). 1594–1612. 13 indexed citations

Li, Kunqian, Li Wu, Qi Qi, et al.. (2022). Beyond Single Reference for Training: Underwater Image Enhancement via Comparative Learning. IEEE Transactions on Circuits and Systems for Video Technology. 33(6). 2561–2576. 103 indexed citations

Fu, Xueyang, Qi Qi, Zheng-Jun Zha, Yurui Zhu, & Xinghao Ding. (2021). Rain Streak Removal via Dual Graph Convolutional Network. Proceedings of the AAAI Conference on Artificial Intelligence. 35(2). 1352–1360. 83 indexed citations

10.

Fu, Xueyang, Qi Qi, Zheng-Jun Zha, et al.. (2021). Successive Graph Convolutional Network for Image De-raining. International Journal of Computer Vision. 129(5). 1691–1711. 39 indexed citations

11.

Qi, Qi, Yongchang Zhang, Fei Tian, et al.. (2021). Underwater Image Co-Enhancement With Correlation Feature Matching and Joint Learning. IEEE Transactions on Circuits and Systems for Video Technology. 32(3). 1133–1147. 121 indexed citations

12.

Qi, Qi, Kunqian Li, Xinning Wang, Xin Luan, & Dalei Song. (2020). DrlNet: Blind object proposal quality assessment with discriminative response learning. Digital Signal Processing. 106. 102810–102810.

13.

Wang, Hongfen, Qi Qi, Yongxing Zhang, et al.. (2020). Anticorrosive Epoxy Nanocomposite Coatings Filled with Polyaniline-Functionalized Silicon Nitride Particles. Industrial & Engineering Chemistry Research. 59(38). 16649–16659. 18 indexed citations

14.

Qi, Qi, et al.. (2019). High-speed video salient object detection with temporal propagation using correlation filter. Neurocomputing. 356. 107–118. 4 indexed citations

15.

Qi, Qi, Sanyuan Zhao, Jianbing Shen, & Kin‐Man Lam. (2019). Multi-scale Capsule Attention-Based Salient Object Detection with Multi-crossed Layer Connections. PolyU Institutional Research Archive (Hong Kong Polytechnic University). 1762–1767. 17 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.

Explore authors with similar magnitude of impact