Junru Wu

1.9k total citations · 1 hit paper
10 papers, 961 citations indexed

About

Junru Wu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Human-Computer Interaction. According to data from OpenAlex, Junru Wu has authored 10 papers receiving a total of 961 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 3 papers in Human-Computer Interaction. Recurrent topics in Junru Wu's work include Visual Attention and Saliency Detection (3 papers), Gaze Tracking and Assistive Technology (3 papers) and Topic Modeling (2 papers). Junru Wu is often cited by papers focused on Visual Attention and Saliency Detection (3 papers), Gaze Tracking and Assistive Technology (3 papers) and Topic Modeling (2 papers). Junru Wu collaborates with scholars based in United States, China and Ukraine. Junru Wu's co-authors include Zhangyang Wang, Tetiana Martyniuk, Orest Kupyn, Shenghua Gao, Yanyu Xu, Jingyi Yu, Zhiru Shi, Nianyi Li, Honglei Zhuang and Xuanhui Wang and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, The HKU Scholars Hub (University of Hong Kong) and International Conference on Machine Learning.

In The Last Decade

Junru Wu

8 papers receiving 936 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.

DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better

2019 639 citations Orest Kupyn, Tetiana Martyniuk et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Junru Wu United States	7	833	309	82	76	63	10	961
Santosh Kumar Vipparthi India	18	606 0.7×	110 0.4×	117 1.4×	107 1.4×	43 0.7×	56	815
Tarik Arici United States	10	881 1.1×	338 1.1×	54 0.7×	100 1.3×	72 1.1×	16	1.1k
Srirangaraj Setlur United States	17	732 0.9×	190 0.6×	205 2.5×	64 0.8×	119 1.9×	81	948
Koki Nagano United States	19	1.4k 1.7×	130 0.4×	153 1.9×	97 1.3×	76 1.2×	45	1.7k
Jianyi Wang China	9	496 0.6×	142 0.5×	64 0.8×	29 0.4×	77 1.2×	25	663
Yixin Chen China	14	477 0.6×	141 0.5×	107 1.3×	43 0.6×	22 0.3×	33	646
Jie Zou China	12	318 0.4×	137 0.4×	133 1.6×	31 0.4×	70 1.1×	43	613
Xiang Ma China	14	652 0.8×	262 0.8×	96 1.2×	21 0.3×	35 0.6×	40	807
Vassilios Vonikakis Singapore	13	593 0.7×	147 0.5×	142 1.7×	23 0.3×	42 0.7×	29	834
Adıń Ramıŕez Rivera Brazil	11	755 0.9×	90 0.3×	125 1.5×	39 0.5×	87 1.4×	30	917

Countries citing papers authored by Junru Wu

Since Specialization

Citations

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

Fields of papers citing papers by Junru Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Junru Wu

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

10 of 10 papers shown

1.

Wu, Junru, et al.. (2025). C²RBench: A Chinese Complex Reasoning Benchmark for Large Language Models. 21031–21050.

2.

Liu, Tianqi, Zhen Qin, Junru Wu, et al.. (2025). LiPO: Listwise Preference Optimization through Learning-to-Rank. 2404–2420. 1 indexed citations

3.

Zhuang, Honglei, Zhen Qin, Kai Hui, et al.. (2024). Beyond Yes and No: Improving Zero-Shot LLM Rankers via Scoring Fine-Grained Relevance Labels. 358–370. 11 indexed citations

4.

Qin, Zhen, Rolf Jagerman, Kai Hui, et al.. (2024). Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting. 1504–1518. 46 indexed citations

5.

Wu, Junru, et al.. (2020). DAVID: Dual-Attentional Video Deblurring. 2365–2374. 17 indexed citations

6.

Kupyn, Orest, Tetiana Martyniuk, Junru Wu, & Zhangyang Wang. (2019). DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better. 8877–8886. 639 indexed citations breakdown →

7.

Wu, Junru, et al.. (2018). Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions. International Conference on Machine Learning. 5359–5368. 6 indexed citations

8.

Xu, Yanyu, et al.. (2018). Gaze Prediction in Dynamic 360° Immersive Videos. The HKU Scholars Hub (University of Hong Kong). 5333–5342. 189 indexed citations

9.

Xu, Yanyu, Shenghua Gao, Junru Wu, Nianyi Li, & Jingyi Yu. (2018). Personalized Saliency and Its Prediction. IEEE Transactions on Pattern Analysis and Machine Intelligence. 41(12). 2975–2989. 35 indexed citations

10.

Xu, Yanyu, Nianyi Li, Junru Wu, Jingyi Yu, & Shenghua Gao. (2017). Beyond Universal Saliency: Personalized Saliency Prediction with Multi-task CNN. 3887–3893. 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.

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