Quanquan Li

1.1k total citations · 1 hit paper
9 papers, 612 citations indexed

About

Quanquan Li is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Molecular Biology. According to data from OpenAlex, Quanquan Li has authored 9 papers receiving a total of 612 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 4 papers in Artificial Intelligence and 1 paper in Molecular Biology. Recurrent topics in Quanquan Li's work include Advanced Neural Network Applications (4 papers), Advanced Image and Video Retrieval Techniques (3 papers) and Video Surveillance and Tracking Methods (2 papers). Quanquan Li is often cited by papers focused on Advanced Neural Network Applications (4 papers), Advanced Image and Video Retrieval Techniques (3 papers) and Video Surveillance and Tracking Methods (2 papers). Quanquan Li collaborates with scholars based in China, Australia and Germany. Quanquan Li's co-authors include Jingru Tan, Changqing Yin, Wanli Ouyang, Junjie Yan, Buyu Li, Changbao Wang, Xin Lu, Gang Zhang, Hongsheng Li and Xiaogang Wang and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Cybernetics and Chinese Physics B.

In The Last Decade

Quanquan Li

9 papers receiving 599 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.

Equalization Loss for Long-Tailed Object Recognition

2020 281 citations Jingru Tan, Changbao Wang et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Quanquan Li China	5	386	304	56	48	35	9	612
Jinpeng Li China	13	412 1.1×	165 0.5×	77 1.4×	59 1.2×	38 1.1×	43	702
Ruihuang Li Hong Kong	12	613 1.6×	307 1.0×	96 1.7×	37 0.8×	20 0.6×	16	777
Anurag Arnab United States	12	669 1.7×	364 1.2×	46 0.8×	38 0.8×	12 0.3×	28	880
Renrui Zhang China	10	453 1.2×	312 1.0×	45 0.8×	50 1.0×	10 0.3×	18	732
Lars Mescheder Germany	7	486 1.3×	135 0.4×	29 0.5×	17 0.4×	38 1.1×	8	630
Zhiwu Lu China	15	626 1.6×	358 1.2×	44 0.8×	46 1.0×	25 0.7×	30	839
Sedat Özer Türkiye	12	264 0.7×	107 0.4×	38 0.7×	73 1.5×	41 1.2×	31	482
Huan Xiong China	12	386 1.0×	233 0.8×	45 0.8×	54 1.1×	6 0.2×	57	664
Hamed Habibi Aghdam Spain	8	200 0.5×	118 0.4×	77 1.4×	16 0.3×	21 0.6×	20	410

Countries citing papers authored by Quanquan Li

Since Specialization

Citations

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

Fields of papers citing papers by Quanquan Li

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Quanquan Li

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

9 of 9 papers shown

1.

Li, Quanquan, et al.. (2024). RALACs: Action Recognition in Autonomous Vehicles Using Interaction Encoding and Optical Flow. IEEE Transactions on Cybernetics. 55(2). 512–525. 2 indexed citations

2.

Zhang, Gang, Xin Lu, Jingru Tan, et al.. (2021). RefineMask: Towards High-Quality Instance Segmentation with Fine-Grained Features. 6857–6865. 91 indexed citations

3.

Tan, Jingru, Xin Lu, Gang Zhang, Changqing Yin, & Quanquan Li. (2021). Equalization Loss v2: A New Gradient Balance Approach for Long-tailed Object Detection. 1685–1694. 106 indexed citations

4.

Tan, Jingru, Changbao Wang, Buyu Li, et al.. (2020). Equalization Loss for Long-Tailed Object Recognition. 11659–11668. 281 indexed citations breakdown →

5.

Yuan, Kun, Quanquan Li, Yucong Zhou, Jing Shao, & Junjie Yan. (2019). Diving into Optimization of Topology in Neural Networks. 1 indexed citations

6.

Li, Quanquan, Xuemei Xu, Linzi Yin, et al.. (2018). Implication of two-coupled tri-stable stochastic resonance in weak signal detection. Chinese Physics B. 27(3). 34203–34203. 23 indexed citations

7.

Gao, Wei, Wei Yi, Quanquan Li, et al.. (2018). PRUNING WITH HINTS: AN EFFICIENT FRAMEWORK FOR MODEL ACCELERATION. 1 indexed citations

8.

Ouyang, Wanli, Hui Zhou, Hongsheng Li, et al.. (2017). Jointly Learning Deep Features, Deformable Parts, Occlusion and Classification for Pedestrian Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence. 40(8). 1874–1887. 106 indexed citations

9.

Li, Quanquan, et al.. (2013). An optimized hardware architecture for intra prediction in H.264 decoder. 3. 1–4. 1 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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