Feng Wu

2.0k total citations · 1 hit paper
74 papers, 1.3k citations indexed

About

Feng Wu is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Computer Networks and Communications. According to data from OpenAlex, Feng Wu has authored 74 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Computer Vision and Pattern Recognition, 21 papers in Signal Processing and 12 papers in Computer Networks and Communications. Recurrent topics in Feng Wu's work include Video Coding and Compression Technologies (17 papers), Advanced Data Compression Techniques (15 papers) and Advanced Vision and Imaging (11 papers). Feng Wu is often cited by papers focused on Video Coding and Compression Technologies (17 papers), Advanced Data Compression Techniques (15 papers) and Advanced Vision and Imaging (11 papers). Feng Wu collaborates with scholars based in China, United States and Singapore. Feng Wu's co-authors include Shipeng Li, Ya-Qin Zhang, Tianzhu Zhang, Xi Wei, Yan Li, Yongdong Zhang, Daqing Liu, Zheng-Jun Zha, Hanwang Zhang and Dong Liu and has published in prestigious journals such as Nature Communications, IEEE Transactions on Image Processing and Optics Express.

In The Last Decade

Feng Wu

64 papers receiving 1.3k citations

Hit Papers

Multi-Modality Cross Attention Network for Image and Sent... 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. Multi-Modality Cross Attention Network for Image and Sentence Matching
    2020 271 citations Tianzhu Zhang, Feng Wu 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
Feng Wu China 16 995 416 287 157 132 74 1.3k
Gwo‐Jong Yu Taiwan 10 1.0k 1.0× 328 0.8× 279 1.0× 222 1.4× 138 1.0× 30 1.5k
Ioannis Katsavounidis United States 15 1.0k 1.0× 416 1.0× 171 0.6× 63 0.4× 55 0.4× 55 1.3k
Min Long China 25 1.4k 1.5× 389 0.9× 254 0.9× 87 0.6× 108 0.8× 105 1.8k
Olivier Déforges France 18 821 0.8× 344 0.8× 220 0.8× 63 0.4× 90 0.7× 106 1.1k
Chaur‐Heh Hsieh Taiwan 18 867 0.9× 524 1.3× 164 0.6× 67 0.4× 202 1.5× 85 1.2k
Tammam Tillo China 19 1.2k 1.2× 522 1.3× 117 0.4× 164 1.0× 182 1.4× 87 1.4k
Debargha Mukherjee United States 22 1.6k 1.6× 896 2.2× 130 0.5× 90 0.6× 135 1.0× 114 1.8k
Bilge Günsel Türkiye 19 713 0.7× 349 0.8× 146 0.5× 39 0.2× 44 0.3× 89 978
Anthony T. S. Ho United Kingdom 21 1.4k 1.4× 443 1.1× 151 0.5× 79 0.5× 329 2.5× 107 2.0k
Jarno Vanne Finland 18 1.3k 1.3× 1.0k 2.5× 61 0.2× 118 0.8× 137 1.0× 91 1.5k

Countries citing papers authored by Feng Wu

Since Specialization
Citations

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

Fields of papers citing papers by Feng Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Feng Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Feng Wu. A scholar is included among the top collaborators of Feng 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 Feng Wu. Feng Wu 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.
2.
Wu, Feng, et al.. (2025). Federated Class-Incremental Learning via Weighted Aggregation and Distillation. IEEE Internet of Things Journal. 12(12). 22489–22503.
3.
Vezzoli, Stefano, T. V. Raziman, C. F. Hooper, et al.. (2025). Space-time optical diffraction from synthetic motion. Nature Communications. 16(1). 5147–5147. 1 indexed citations
4.
Chen, Yuanlu, et al.. (2024). General Federated Class-Incremental Learning With Lightweight Generative Replay. IEEE Internet of Things Journal. 11(20). 33927–33939. 3 indexed citations
5.
6.
Li, Yinsheng, et al.. (2021). A Processing Method of Presenting Indicators Hierarchy and Classification in Spreadsheet. 47. 517–520. 1 indexed citations
7.
Xiong, Ruiqin, et al.. (2020). Graph-Based Non-Convex Low-Rank Regularization for Image Compression Artifact Reduction. IEEE Transactions on Image Processing. 29. 5374–5385. 17 indexed citations
8.
Liu, Daqing, Hanwang Zhang, Zheng-Jun Zha, & Feng Wu. (2019). Learning to Assemble Neural Module Tree Networks for Visual Grounding. 4672–4681. 180 indexed citations
9.
Zhao, Wenbin, et al.. (2019). A two-layer SIR information propagation model with heterogeneity based on coupled network. The Journal of Supercomputing. 76(3). 1657–1679. 4 indexed citations
10.
Meng, Dong, Dong Liu, Zhiwei Xiong, et al.. (2018). 3D Cnn-Based Soma Segmentation from Brain Images at Single-Neuron Resolution. 5 indexed citations
11.
Habachi, Oussama, et al.. (2012). MOS-Based Congestion Control for Conversational Services in Wireless Environments. IEEE Journal on Selected Areas in Communications. 30(7). 1225–1236. 17 indexed citations
12.
Peng, Xiulian, Jizheng Xu, You Zhou, & Feng Wu. (2011). Highly Parallel Line-Based Image Coding for Many Cores. IEEE Transactions on Image Processing. 21(1). 196–206. 10 indexed citations
13.
14.
Wu, Feng, et al.. (2009). Mining Frequent Patterns in Data Stream over Sliding Windows. 1–4. 2 indexed citations
15.
Zhu, Xifang, et al.. (2009). Image restoration for sparse aperture systems based on wavelet-Wiener algorithm. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7513. 75131B–75131B. 3 indexed citations
16.
Luo, Chong, Wei Pu, Chang Wen Chen, Jun Sun, & Feng Wu. (2009). Forepressure Transmission Control for Wireless Video Sensor Networks. 1–9. 1 indexed citations
17.
Liu, Dong, Xiaoyan Sun, Feng Wu, & Yaqin Zhang. (2008). Edge-Oriented Uniform Intra Prediction. IEEE Transactions on Image Processing. 17(10). 1827–1836. 25 indexed citations
18.
Shen, Huifeng, Xiaoyan Sun, & Feng Wu. (2008). Fast H.264/MPEG-4 AVC Transcoding Using Power-Spectrum Based Rate-Distortion Optimization. IEEE Transactions on Circuits and Systems for Video Technology. 18(6). 746–755. 17 indexed citations
19.
Zhang, Dongdong, Wenjun Zhang, Jizheng Xu, Feng Wu, & Hongkai Xiong. (2008). A Cross-Resolution Leaky Prediction Scheme for In-Band Wavelet Video Coding With Spatial Scalability. IEEE Transactions on Circuits and Systems for Video Technology. 18(4). 516–521. 4 indexed citations
20.
Wang, Qi, Feng Wu, Shipeng Li, Yuzhuo Zhong, & Yaqin Zhang. (2002). Fine-granularity spatially scalable video coding. 3. 1801–1804. 7 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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