Gaofeng Meng

6.1k total citations · 3 hit papers
89 papers, 3.7k citations indexed

About

Gaofeng Meng is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence. According to data from OpenAlex, Gaofeng Meng has authored 89 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 70 papers in Computer Vision and Pattern Recognition, 23 papers in Media Technology and 18 papers in Artificial Intelligence. Recurrent topics in Gaofeng Meng's work include Advanced Image and Video Retrieval Techniques (19 papers), Advanced Vision and Imaging (16 papers) and Advanced Neural Network Applications (15 papers). Gaofeng Meng is often cited by papers focused on Advanced Image and Video Retrieval Techniques (19 papers), Advanced Vision and Imaging (16 papers) and Advanced Neural Network Applications (15 papers). Gaofeng Meng collaborates with scholars based in China, India and United States. Gaofeng Meng's co-authors include Chunhong Pan, Shiming Xiang, Jiangyong Duan, Ying Wang, Jianlong Chang, Lingfeng Wang, Changshui Zhang, Shiming Xiang, Feiping Nie and Chunhong Pan and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Pattern Recognition.

In The Last Decade

Gaofeng Meng

84 papers receiving 3.6k citations

Hit Papers

Efficient Image Dehazing with Boundary Constraint and Con... 2012 2026 2016 2021 2013 2012 2019 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gaofeng Meng China 27 2.6k 1.1k 779 332 253 89 3.7k
Samuel Rota Bulò Italy 29 2.1k 0.8× 234 0.2× 1.3k 1.7× 255 0.8× 89 0.4× 79 3.3k
Ming-Yu Liu United States 26 6.4k 2.4× 1.2k 1.1× 1.2k 1.5× 711 2.1× 100 0.4× 73 8.2k
Xiao Bai China 40 2.9k 1.1× 973 0.9× 1.5k 1.9× 363 1.1× 43 0.2× 161 4.9k
Dengxin Dai Switzerland 32 3.3k 1.2× 822 0.8× 1.8k 2.3× 228 0.7× 144 0.6× 91 4.8k
Timo Rehfeld Germany 6 5.6k 2.1× 656 0.6× 2.4k 3.1× 77 0.2× 169 0.7× 8 7.0k
Marius Cordts Germany 7 5.7k 2.2× 660 0.6× 2.4k 3.1× 77 0.2× 173 0.7× 16 7.1k
Jianke Zhu China 31 2.9k 1.1× 432 0.4× 1.1k 1.4× 146 0.4× 61 0.2× 109 4.1k
Miguel Á. Carreira-Perpiñán United States 27 1.8k 0.7× 242 0.2× 1.3k 1.7× 200 0.6× 269 1.1× 106 3.4k
Sebastian Ramos Spain 9 5.9k 2.2× 676 0.6× 2.5k 3.2× 77 0.2× 173 0.7× 12 7.3k
Fan Zhu China 29 2.5k 0.9× 250 0.2× 1.5k 1.9× 382 1.2× 36 0.1× 76 3.7k

Countries citing papers authored by Gaofeng Meng

Since Specialization
Citations

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

Fields of papers citing papers by Gaofeng Meng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gaofeng Meng

This figure shows the co-authorship network connecting the top 25 collaborators of Gaofeng Meng. A scholar is included among the top collaborators of Gaofeng Meng 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 Gaofeng Meng. Gaofeng Meng 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.
Zhang, Chi, et al.. (2024). DDGPnP: Differential degree graph based PnP solution to handle outliers. Computer Vision and Image Understanding. 248. 104130–104130. 1 indexed citations
2.
Meng, Gaofeng, et al.. (2024). Defying Imbalanced Forgetting in Class Incremental Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 38(14). 16211–16219.
3.
Meng, Gaofeng, et al.. (2024). Reusable Architecture Growth for Continual Stereo Matching. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(9). 6167–6184. 3 indexed citations
4.
Xu, Shixiong, et al.. (2024). MoBoo: Memory-Boosted Vision Transformer for Class-Incremental Learning. IEEE Transactions on Circuits and Systems for Video Technology. 34(11). 11169–11183. 5 indexed citations
5.
Chang, Jianlong, et al.. (2023). Pro-Tuning: Unified Prompt Tuning for Vision Tasks. IEEE Transactions on Circuits and Systems for Video Technology. 34(6). 4653–4667. 34 indexed citations
6.
Xiao, Xinyu, et al.. (2023). SpatioTemporal Inference Network for Precipitation Nowcasting With Multimodal Fusion. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 17. 1299–1314. 16 indexed citations
8.
Zhou, Shengchao, Gaofeng Meng, Zhaoxiang Zhang, Richard Yi Da Xu, & Shiming Xiang. (2023). Robust Feature Rectification of Pretrained Vision Models for Object Recognition. Proceedings of the AAAI Conference on Artificial Intelligence. 37(3). 3796–3804.
9.
Liu, Xiyan, et al.. (2021). Decoupled Representation Learning for Character Glyph Synthesis. IEEE Transactions on Multimedia. 24. 1787–1799. 8 indexed citations
10.
Chang, Jianlong, Yiwen Guo, Gaofeng Meng, et al.. (2020). DATA: Differentiable ArchiTecture Approximation With Distribution Guided Sampling. IEEE Transactions on Pattern Analysis and Machine Intelligence. 43(9). 2905–2920. 11 indexed citations
11.
Chen, Yukang, Peizhen Zhang, Zeming Li, et al.. (2020). Stitcher: Feedback-driven Data Provider for Object Detection. arXiv (Cornell University). 31 indexed citations
12.
Liu, Xiyan, Gaofeng Meng, Bin Fan, Shiming Xiang, & Chunhong Pan. (2020). Geometric rectification of document images using adversarial gated unwarping network. Pattern Recognition. 108. 107576–107576. 22 indexed citations
13.
Gu, Jie, Gaofeng Meng, Shiming Xiang, & Chunhong Pan. (2019). Blind image quality assessment via learnable attention-based pooling. Pattern Recognition. 91. 332–344. 34 indexed citations
14.
Chen, Yukang, Tong Yang, Xiangyu Zhang, et al.. (2019). DetNAS: Neural Architecture Search on Object Detection.. arXiv (Cornell University). 46 indexed citations
15.
Chang, Jianlong, et al.. (2019). DATA: Differentiable ArchiTecture Approximation. Neural Information Processing Systems. 32. 874–884. 25 indexed citations
16.
Chang, Jianlong, Lingfeng Wang, Gaofeng Meng, Shiming Xiang, & Chunhong Pan. (2018). Vision-Based Occlusion Handling and Vehicle Classification for Traffic Surveillance Systems. IEEE Intelligent Transportation Systems Magazine. 10(2). 80–92. 42 indexed citations
17.
Chang, Jianlong, Gaofeng Meng, Lingfeng Wang, Shiming Xiang, & Chunhong Pan. (2018). Deep Self-Evolution Clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence. 42(4). 809–823. 65 indexed citations
18.
Ren, Wenqi, Jingang Zhang, Xiangyu Xu, et al.. (2018). Deep Video Dehazing With Semantic Segmentation. IEEE Transactions on Image Processing. 28(4). 1895–1908. 152 indexed citations
19.
Chang, Jianlong, Jie Gu, Lingfeng Wang, et al.. (2018). Structure-Aware Convolutional Neural Networks. Neural Information Processing Systems. 31. 11–20. 19 indexed citations
20.
Gu, Jie, Gaofeng Meng, Judith Redi, Shiming Xiang, & Chunhong Pan. (2017). Blind Image Quality Assessment via Vector Regression and Object Oriented Pooling. IEEE Transactions on Multimedia. 20(5). 1140–1153. 35 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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