Jingjing Liu

6.9k total citations · 3 hit papers
70 papers, 2.7k citations indexed

About

Jingjing Liu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Jingjing Liu has authored 70 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Computer Vision and Pattern Recognition, 27 papers in Artificial Intelligence and 5 papers in Media Technology. Recurrent topics in Jingjing Liu's work include Multimodal Machine Learning Applications (20 papers), Advanced Neural Network Applications (16 papers) and Domain Adaptation and Few-Shot Learning (12 papers). Jingjing Liu is often cited by papers focused on Multimodal Machine Learning Applications (20 papers), Advanced Neural Network Applications (16 papers) and Domain Adaptation and Few-Shot Learning (12 papers). Jingjing Liu collaborates with scholars based in China, United States and United Kingdom. Jingjing Liu's co-authors include Zhe Gan, Linjie Li, Yu Cheng, Shaoting Zhang, Shu Wang, Dimitris Metaxas, Chuanyang Liu, Luowei Zhou, Licheng Yu and Jie Lei and has published in prestigious journals such as PLoS ONE, International Journal of Hydrogen Energy and Materials Science and Engineering A.

In The Last Decade

Jingjing Liu

64 papers receiving 2.6k citations

Hit Papers

Less is More: CLIPBERT for Video-and-Langua... 2016 2026 2019 2022 2021 2016 2020 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jingjing Liu China 25 2.0k 1.1k 193 189 137 70 2.7k
Guoliang Kang China 14 2.9k 1.4× 1.7k 1.6× 231 1.2× 143 0.8× 88 0.6× 36 4.0k
Hongyuan Zhu Singapore 27 2.0k 1.0× 1.1k 1.0× 382 2.0× 125 0.7× 53 0.4× 77 2.8k
Zhiqiang Shen United States 17 2.2k 1.1× 1.4k 1.3× 241 1.2× 206 1.1× 53 0.4× 34 2.9k
Yingwei Pan China 29 3.3k 1.6× 1.4k 1.3× 162 0.8× 135 0.7× 53 0.4× 85 4.0k
Zhenmin Tang China 27 1.3k 0.7× 872 0.8× 210 1.1× 124 0.7× 53 0.4× 221 2.6k
Yun Xiao China 14 829 0.4× 675 0.6× 183 0.9× 176 0.9× 62 0.5× 60 1.8k
BoRui Wu United States 17 1.9k 0.9× 1.3k 1.2× 146 0.8× 265 1.4× 42 0.3× 42 2.8k
Quanfu Fan United States 18 1.3k 0.6× 587 0.5× 251 1.3× 132 0.7× 42 0.3× 48 2.1k

Countries citing papers authored by Jingjing Liu

Since Specialization
Citations

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

Fields of papers citing papers by Jingjing Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jingjing Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Jingjing Liu. A scholar is included among the top collaborators of Jingjing Liu 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 Jingjing Liu. Jingjing Liu 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.
Liu, Jingjing, et al.. (2025). SSDM: Generated image interaction method based on spatial sparsity for diffusion models. Neurocomputing. 634. 129805–129805.
2.
Liu, Jingjing, et al.. (2023). Moving object detection in gigapixel-level videos using manifold sparse representation. Multimedia Tools and Applications. 83(6). 18381–18405. 2 indexed citations
3.
Liu, Jingjing, et al.. (2023). Automatic detection of fastener safety wire twisting direction based on machine vision. 15–15. 2 indexed citations
4.
Yao, Yuyou, et al.. (2023). Accelerating surface remeshing through GPU-based computation of the restricted tangent face. Computer Aided Geometric Design. 104. 102216–102216. 2 indexed citations
5.
Liu, Jingjing, et al.. (2023). CCTSS: The Combination of CNN and Transformer with Shared Sublayer for Detection and Classification. IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences. E107.A(1). 141–156.
6.
Li, Linjie, Jie Lei, Zhe Gan, et al.. (2021). VALUE: A Multi-Task Benchmark for Video-and-Language Understanding Evaluation. arXiv (Cornell University). 1 indexed citations
7.
Lei, Jie, Linjie Li, Luowei Zhou, et al.. (2021). Less is More: CLIPBERT for Video-and-Language Learning via Sparse Sampling. 7327–7337. 372 indexed citations breakdown →
8.
Liu, Jingjing, et al.. (2021). An Improved Method Based on Deep Learning for Insulator Fault Detection in Diverse Aerial Images. Energies. 14(14). 4365–4365. 40 indexed citations
9.
Liu, Jingzhou, Wenhu Chen, Yu Cheng, et al.. (2020). Violin: A Large-Scale Dataset for Video-and-Language Inference. 10897–10907. 42 indexed citations
10.
Gan, Zhe, Yen-Chun Chen, Linjie Li, et al.. (2020). Large-Scale Adversarial Training for Vision-and-Language Representation Learning. Neural Information Processing Systems. 33. 6616–6628. 15 indexed citations
11.
Li, Linjie, Yen‐Chun Chen, Yu Cheng, et al.. (2020). HERO: Hierarchical Encoder for Video+Language Omni-representation Pre-training. 2046–2065. 265 indexed citations breakdown →
12.
Liu, Jingjing, Yifei Lou, Guoxi Ni, & Tieyong Zeng. (2020). An image sharpening operator combined with framelet for image deblurring. Inverse Problems. 36(4). 45015–45015. 19 indexed citations
13.
Hu, Junjie, Yu Cheng, Zhe Gan, et al.. (2020). What Makes A Good Story? Designing Composite Rewards for Visual Storytelling. Proceedings of the AAAI Conference on Artificial Intelligence. 34(5). 7969–7976. 33 indexed citations
14.
Li, Linjie, Zhe Gan, Yu Cheng, & Jingjing Liu. (2019). Relation-Aware Graph Attention Network for Visual Question Answering. 10312–10321. 241 indexed citations
15.
Liu, Jingjing, Lin Zhou, & Li Zhao. (2019). Advanced wang–landau monte carlo‐based tracker for abrupt motions. IEEJ Transactions on Electrical and Electronic Engineering. 14(6). 877–883. 1 indexed citations
16.
Cheng, Yu, Zhe Gan, Yitong Li, Jingjing Liu, & Jianfeng Gao. (2018). Sequential Attention GAN for Interactive Image Editing via Dialogue.. arXiv (Cornell University). 15 indexed citations
17.
Su, Shang‐Yu, Xiujun Li, Jianfeng Gao, Jingjing Liu, & Yun-Nung Chen. (2018). Discriminative Deep Dyna-Q: Robust Planning for Dialogue Policy Learning. 3813–3823. 39 indexed citations
18.
Liu, Jingjing. (2017). Exploiting multispectral and contextual information to improve human detection. Rutgers University Community Repository (Rutgers University). 1 indexed citations
19.
Liu, Bo, Jingjing Liu, Yu Xiang, Dimitris Metaxas, & Carol Neidle. (2014). 3D Face Tracking and Multi-Scale, Spatio-temporal Analysis of Linguistically Significant Facial Expressions and Head Positions in ASL. Language Resources and Evaluation. 4512–4518. 1 indexed citations
20.
Shi, Yuying, Yonggui Zhu, & Jingjing Liu. (2013). Semi-implicit Image Denoising Algorithm for Different Boundary Conditions. TELKOMNIKA Indonesian Journal of Electrical Engineering. 11(4). 3 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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