Mingbao Lin

2.7k total citations · 1 hit paper
42 papers, 1.4k citations indexed

About

Mingbao Lin is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Mingbao Lin has authored 42 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Computer Vision and Pattern Recognition, 18 papers in Artificial Intelligence and 5 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Mingbao Lin's work include Advanced Neural Network Applications (18 papers), Domain Adaptation and Few-Shot Learning (15 papers) and Advanced Image and Video Retrieval Techniques (8 papers). Mingbao Lin is often cited by papers focused on Advanced Neural Network Applications (18 papers), Domain Adaptation and Few-Shot Learning (15 papers) and Advanced Image and Video Retrieval Techniques (8 papers). Mingbao Lin collaborates with scholars based in China, United Arab Emirates and United States. Mingbao Lin's co-authors include Rongrong Ji, Yonghong Tian, Baochang Zhang, Ling Shao, Yichen Zhang, Yan Wang, Yongjian Wu, Hong Liu, Yuxin Zhang and Shaojie Li 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

Mingbao Lin

36 papers receiving 1.4k citations

Hit Papers

HRank: Filter Pruning Using High-Rank Feature Map 2020 2026 2022 2024 2020 100 200 300 400 500
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. HRank: Filter Pruning Using High-Rank Feature Map
    2020 537 citations Mingbao Lin, Rongrong Ji 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
Mingbao Lin China 18 1.1k 748 97 88 70 42 1.4k
Jian-Hao Luo China 6 1.4k 1.3× 1.0k 1.4× 136 1.4× 89 1.0× 80 1.1× 9 1.8k
Xiaoshan Yang China 21 969 0.9× 553 0.7× 43 0.4× 95 1.1× 47 0.7× 84 1.4k
Ruihao Gong China 14 751 0.7× 666 0.9× 257 2.6× 76 0.9× 79 1.1× 34 1.2k
Fengwei Yu China 11 822 0.7× 534 0.7× 165 1.7× 136 1.5× 46 0.7× 18 1.2k
Zhilan Hu China 9 1.3k 1.1× 573 0.8× 65 0.7× 42 0.5× 35 0.5× 14 1.4k
Gagandeep Singh India 17 580 0.5× 721 1.0× 136 1.4× 216 2.5× 52 0.7× 55 1.3k
Zhenwen Ren China 21 1.2k 1.1× 804 1.1× 37 0.4× 205 2.3× 71 1.0× 108 1.6k
Shikui Wei China 19 1.2k 1.0× 412 0.6× 70 0.7× 140 1.6× 19 0.3× 78 1.5k

Countries citing papers authored by Mingbao Lin

Since Specialization
Citations

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

Fields of papers citing papers by Mingbao Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mingbao Lin

This figure shows the co-authorship network connecting the top 25 collaborators of Mingbao Lin. A scholar is included among the top collaborators of Mingbao Lin 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 Mingbao Lin. Mingbao Lin 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.
Lin, Mingbao, et al.. (2025). UniVST: A Unified Framework for Training-Free Localized Video Style Transfer. IEEE Transactions on Pattern Analysis and Machine Intelligence. 48(3). 2820–2836. 1 indexed citations
3.
Lin, Mingbao, et al.. (2025). I&S-ViT: An Inclusive & Stable Method for Post-Training ViTs Quantization. IEEE Transactions on Pattern Analysis and Machine Intelligence. 48(2). 1063–1080.
4.
Lin, Mingbao, Yixin Cao, Wei Tang, et al.. (2024). LLMs-as-Instructors: Learning from Errors Toward Automating Model Improvement. 11185–11208. 1 indexed citations
5.
Lin, Mingbao, et al.. (2024). Study on the Ratio and Model Test of Similar Materials of Heavily Weathered Granite. Materials. 17(21). 5324–5324. 2 indexed citations
6.
Li, Yanjing, Sheng Xu, Mingbao Lin, et al.. (2024). Bi-ViT: Pushing the Limit of Vision Transformer Quantization. Proceedings of the AAAI Conference on Artificial Intelligence. 38(4). 3243–3251. 4 indexed citations
7.
Lin, Mingbao, et al.. (2024). AnySR: Realizing Image Super-Resolution as Any-Scale, Any-Resource. IEEE Transactions on Image Processing. 33. 6564–6578. 3 indexed citations
8.
Xu, Sheng, Yanjing Li, Mingbao Lin, et al.. (2023). Q-DETR: An Efficient Low-Bit Quantized Detection Transformer. 3842–3851. 15 indexed citations
9.
Lin, Mingbao, et al.. (2023). Prioritized Subnet Sampling for Resource-Adaptive Supernet Training. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(9). 11108–11119. 2 indexed citations
10.
Lin, Mingbao, Ke Li, Yunhang Shen, et al.. (2023). CF-ViT: A General Coarse-to-Fine Method for Vision Transformer. Proceedings of the AAAI Conference on Artificial Intelligence. 37(6). 7042–7052. 39 indexed citations
11.
Wu, Mingrui, et al.. (2023). End-to-End Zero-Shot HOI Detection via Vision and Language Knowledge Distillation. Proceedings of the AAAI Conference on Artificial Intelligence. 37(3). 2839–2846. 19 indexed citations
12.
Lin, Mingbao, et al.. (2023). Shadow-aware dynamic convolution for shadow removal. Pattern Recognition. 146. 109969–109969. 15 indexed citations
13.
Xu, Sheng, Yanjing Li, Mingbao Lin, et al.. (2023). Resilient Binary Neural Network. Proceedings of the AAAI Conference on Artificial Intelligence. 37(9). 10620–10628. 12 indexed citations
14.
Lin, Mingbao, et al.. (2023). Training Compact CNNs for Image Classification Using Dynamic-Coded Filter Fusion. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(8). 10478–10487. 12 indexed citations
15.
Lin, Mingbao, et al.. (2023). SMMix: Self-Motivated Image Mixing for Vision Transformers. 17214–17224. 4 indexed citations
16.
Li, Yanjing, et al.. (2023). Representation Disparity-aware Distillation for 3D Object Detection. 6692–6701. 3 indexed citations
17.
Hu, Tie, et al.. (2023). Discriminator-Cooperated Feature Map Distillation for GAN Compression. 20351–20360. 11 indexed citations
18.
Lin, Mingbao, Rongrong Ji, Baochang Zhang, et al.. (2022). SiMaN: Sign-to-Magnitude Network Binarization. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(5). 6277–6288. 12 indexed citations
19.
Lin, Mingbao, Rongrong Ji, Chen Shen, Xiaoshuai Sun, & Chia‐Wen Lin. (2020). Similarity-Preserving Linkage Hashing for Online Image Retrieval. IEEE Transactions on Image Processing. 29. 5289–5300. 43 indexed citations
20.
Lin, Mingbao, Rongrong Ji, Yuxin Zhang, et al.. (2020). Channel Pruning via Automatic Structure Search. 673–679. 160 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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