Longguang Wang

4.8k total citations · 2 hit papers
73 papers, 2.4k citations indexed

About

Longguang Wang is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Aerospace Engineering. According to data from OpenAlex, Longguang Wang has authored 73 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 59 papers in Computer Vision and Pattern Recognition, 16 papers in Media Technology and 14 papers in Aerospace Engineering. Recurrent topics in Longguang Wang's work include Advanced Vision and Imaging (29 papers), Advanced Image Processing Techniques (25 papers) and Image Processing Techniques and Applications (13 papers). Longguang Wang is often cited by papers focused on Advanced Vision and Imaging (29 papers), Advanced Image Processing Techniques (25 papers) and Image Processing Techniques and Applications (13 papers). Longguang Wang collaborates with scholars based in China, Japan and Australia. Longguang Wang's co-authors include Yingqian Wang, Wei An, Yulan Guo, Jungang Yang, Yulan Guo, Zaiping Lin, Xinyi Ying, Xiaoyu Dong, Boyang Li and Zaiping Lin and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Power Electronics and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

Longguang Wang

65 papers receiving 2.3k 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.

Dense Nested Attention Network for Infrared Small Target Detection

2022 508 citations Boyang Li, Longguang Wang et al. IEEE Transactions on Image Processing profile →
Unsupervised Degradation Representation Learning for Blind Super-Resolution

2021 253 citations Longguang Wang, Yingqian Wang et al. profile →

Peers

Longguang Wang

CVPR

MT

AE

EEE

MM

Yi Chang China

Jungang Yang China

Jie Guo China

In-So Kweon South Korea

Yimian Dai China

Houzhang Fang China

Kan Ren China

Chao Xiao China

Lizhen Deng China

Yi Chang China

Longguang Wang

1.7k ×1.1

CVPR

1.2k ×1.4

MT

388 ×0.6

AE

215 ×0.4

EEE

81 ×0.7

MM

Citations per year, relative to Longguang Wang Longguang Wang (= 1×) peers Yi Chang

Countries citing papers authored by Longguang Wang

Since Specialization

Citations

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

Fields of papers citing papers by Longguang Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Longguang Wang

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

20 of 20 papers shown

1.

Zhang, Jiehua, Longguang Wang, Lian Xu, et al.. (2025). CompletionMamba: Taming State Space Model for Point Cloud Completion. IEEE Transactions on Image Processing. 34. 5473–5485.

2.

Guo, Yulan, et al.. (2025). Deep Lookup Network. IEEE Transactions on Pattern Analysis and Machine Intelligence. 48(1). 202–218.

3.

Li, Boyang, Yingqian Wang, Xinyi Ying, et al.. (2025). Motion and Appearance Decoupling Representation for Event Cameras. IEEE Transactions on Image Processing. 34. 5964–5977. 1 indexed citations

4.

Wang, Yun, et al.. (2025). ADStereo: Efficient Stereo Matching With Adaptive Downsampling and Disparity Alignment. IEEE Transactions on Image Processing. 34. 1204–1218.

5.

Wang, Longguang, et al.. (2025). Enhancing Event-Based Video Reconstruction With Bidirectional Temporal Information. IEEE Transactions on Multimedia. 27. 4831–4843.

6.

Wang, Longguang, et al.. (2024). Tangram-Splatting: Optimizing 3D Gaussian Splatting Through Tangram-inspired Shape Priors. 3075–3083. 1 indexed citations

7.

Wang, Longguang, Yulan Guo, Yingqian Wang, et al.. (2024). Unsupervised Degradation Representation Learning for Unpaired Restoration of Images and Point Clouds. IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(1). 1–18. 6 indexed citations

8.

Zheng, Huicheng, et al.. (2024). Adaptive Sparse Memory Networks for Efficient and Robust Video Object Segmentation. IEEE Transactions on Neural Networks and Learning Systems. 36(2). 3820–3833. 5 indexed citations

9.

Wang, Longguang, et al.. (2024). Point Spatio-Temporal Pyramid Network for Point Cloud Video Understanding. IEEE Signal Processing Letters. 31. 1209–1213. 1 indexed citations

10.

Wang, Longguang, et al.. (2024). Panoptic segmentation of 3D point clouds with Gaussian mixture model in outdoor scenes. 2(1). 7 indexed citations

11.

Guo, Yulan, Hanyun Wang, Longguang Wang, et al.. (2023). 3D Face Recognition: Two Decades of Progress and Prospects. ACM Computing Surveys. 56(3). 1–39. 9 indexed citations

12.

Liu, Hao, et al.. (2023). Self-Supervised Multi-Frame Monocular Depth Estimation for Dynamic Scenes. IEEE Transactions on Circuits and Systems for Video Technology. 34(6). 4989–5001. 5 indexed citations

13.

Li, Boyang, Longguang Wang, Yingqian Wang, et al.. (2023). DDAug: Differentiable Data Augmentation for Weakly Supervised Semantic Segmentation. IEEE Transactions on Multimedia. 26. 4764–4775. 4 indexed citations

14.

Wang, Yun, Longguang Wang, Hanyun Wang, & Yulan Guo. (2022). SPNet: Learning Stereo Matching With Slanted Plane Aggregation. IEEE Robotics and Automation Letters. 7(3). 6258–6265. 8 indexed citations

15.

Wang, Longguang, et al.. (2022). HI-Net: Boosting Self-Supervised Indoor Depth Estimation via Pose Optimization. IEEE Robotics and Automation Letters. 8(1). 224–231. 1 indexed citations

16.

Wang, Longguang, et al.. (2022). SLFNet: A Stereo and LiDAR Fusion Network for Depth Completion. IEEE Robotics and Automation Letters. 7(4). 10605–10612. 6 indexed citations

17.

Wang, Longguang, Yulan Guo, Xiaoyu Dong, et al.. (2022). exploring Fine-Grained Sparsity in Convolutional Neural Networks for Efficient Inference. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(4). 1–18. 6 indexed citations

18.

Wang, Longguang, Yulan Guo, Yingqian Wang, et al.. (2020). Parallax Attention for Unsupervised Stereo Correspondence Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence. 44(4). 2108–2125. 102 indexed citations

19.

Ying, Xinyi, Yingqian Wang, Longguang Wang, et al.. (2020). A Stereo Attention Module for Stereo Image Super-Resolution. IEEE Signal Processing Letters. 27. 496–500. 108 indexed citations

20.

Wang, Longguang, et al.. (2016). Gln attenuates LPS-induced inflammatory injury of Bos taurus testis sustentacular cells.. Journal of Pharmaceutical and Biomedical Sciences. 24(12). 1862. 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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