Kaixuan Wei

918 total citations
14 papers, 548 citations indexed

About

Kaixuan Wei is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Instrumentation. According to data from OpenAlex, Kaixuan Wei has authored 14 papers receiving a total of 548 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computer Vision and Pattern Recognition, 5 papers in Media Technology and 2 papers in Instrumentation. Recurrent topics in Kaixuan Wei's work include Image and Signal Denoising Methods (4 papers), Advanced Image Fusion Techniques (3 papers) and Sparse and Compressive Sensing Techniques (2 papers). Kaixuan Wei is often cited by papers focused on Image and Signal Denoising Methods (4 papers), Advanced Image Fusion Techniques (3 papers) and Sparse and Compressive Sensing Techniques (2 papers). Kaixuan Wei collaborates with scholars based in China, United States and Saudi Arabia. Kaixuan Wei's co-authors include Ying Fu, Hua Huang, Jiaolong Yang, Yinqiang Zheng, Felix Heide, Linwei Chen, Dezhi Zheng, Lixiong Wen, Jiawei Zhang and Ran Tao and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Signal Processing and Science Advances.

In The Last Decade

Kaixuan Wei

13 papers receiving 532 citations

Peers

Kaixuan Wei

CVPR

MT

EEE

BE

CM

Shuochen Su Canada

Weidong Sheng China

Gyanendra Sheoran India

Tao Jin China

Chenyang Lei Hong Kong

Jorge Bacca Colombia

Changyin Zhou China

Takashi Ida Japan

Taeg Sang Cho United States

Xiaowan Hu China

Shuochen Su Canada

Kaixuan Wei

508 ×1.2

CVPR

235 ×0.9

MT

31 ×0.5

EEE

70 ×1.4

BE

16 ×0.4

CM

Citations per year, relative to Kaixuan Wei Kaixuan Wei (= 1×) peers Shuochen Su

Countries citing papers authored by Kaixuan Wei

Since Specialization

Citations

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

Fields of papers citing papers by Kaixuan Wei

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kaixuan Wei

This figure shows the co-authorship network connecting the top 25 collaborators of Kaixuan Wei. A scholar is included among the top collaborators of Kaixuan Wei 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 Kaixuan Wei. Kaixuan Wei is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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14 of 14 papers shown

1.

Sun, Jipeng, Kaixuan Wei, Congli Wang, et al.. (2025). Collaborative On-Sensor Array Cameras. ACM Transactions on Graphics. 44(4). 1–18.

2.

Wei, Kaixuan, Johannes E. Fröch, Praneeth Chakravarthula, et al.. (2024). Spatially varying nanophotonic neural networks. Science Advances. 10(45). eadp0391–eadp0391. 16 indexed citations

3.

Tao, Ran, et al.. (2024). Single-Shot Phase Retrieval From a Fractional Fourier Transform Perspective. IEEE Transactions on Signal Processing. 72. 3303–3317. 5 indexed citations

4.

Chen, Linwei, Ying Fu, Kaixuan Wei, Dezhi Zheng, & Felix Heide. (2023). Instance Segmentation in the Dark. International Journal of Computer Vision. 131(8). 2198–2218. 47 indexed citations

5.

Wei, Kaixuan, et al.. (2023). ∇-Prox: Differentiable Proximal Algorithm Modeling for Large-Scale Optimization. ACM Transactions on Graphics. 42(4). 1–19. 4 indexed citations

6.

Tao, Ran, et al.. (2022). Dynamic proximal unrolling network for compressive imaging. Neurocomputing. 510. 203–217. 10 indexed citations

7.

Wei, Kaixuan, et al.. (2022). Deep plug-and-play prior for hyperspectral image restoration. Neurocomputing. 481. 281–293. 36 indexed citations

8.

Wei, Kaixuan, Ying Fu, Yinqiang Zheng, & Jiaolong Yang. (2021). Physics-based Noise Modeling for Extreme Low-light Photography. IEEE Transactions on Pattern Analysis and Machine Intelligence. 44(11). 1–1. 71 indexed citations

9.

Zhang, Jiawei, et al.. (2021). Microreactor facilitated preparation and Ni-doping of MnO2 nanoparticles for supercapacitors. Journal of Alloys and Compounds. 889. 161772–161772. 30 indexed citations

10.

Hong, Yang, et al.. (2021). Crafting Object Detection in Very Low Light. 7 indexed citations

11.

Wei, Kaixuan, Ying Fu, & Hua Huang. (2020). 3-D Quasi-Recurrent Neural Network for Hyperspectral Image Denoising. IEEE Transactions on Neural Networks and Learning Systems. 32(1). 363–375. 154 indexed citations

12.

Wei, Kaixuan, Ying Fu, Jiaolong Yang, & Hua Huang. (2020). A Physics-Based Noise Formation Model for Extreme Low-Light Raw Denoising. 2755–2764. 146 indexed citations

13.

Wei, Kaixuan & Ying Fu. (2018). Low-rank Bayesian tensor factorization for hyperspectral image denoising. Neurocomputing. 331. 412–423. 21 indexed citations

14.

Wei, Kaixuan, et al.. (2016). Analysis of Jewelry Design Based on Computer Graphics Simulation Technology. International Journal of Hybrid Information Technology. 9(11). 425–436. 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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