Nanyi Fei

520 total citations · 1 hit paper
9 papers, 302 citations indexed

About

Nanyi Fei is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Neurology. According to data from OpenAlex, Nanyi Fei has authored 9 papers receiving a total of 302 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Vision and Pattern Recognition, 4 papers in Artificial Intelligence and 1 paper in Neurology. Recurrent topics in Nanyi Fei's work include Multimodal Machine Learning Applications (4 papers), Domain Adaptation and Few-Shot Learning (4 papers) and Advanced Image and Video Retrieval Techniques (3 papers). Nanyi Fei is often cited by papers focused on Multimodal Machine Learning Applications (4 papers), Domain Adaptation and Few-Shot Learning (4 papers) and Advanced Image and Video Retrieval Techniques (3 papers). Nanyi Fei collaborates with scholars based in China, United Kingdom and Hong Kong. Nanyi Fei's co-authors include Tao Xiang, Zhiwu Lu, Haoyu Lu, Yuqi Huo, Yizhao Gao, Ji-Rong Wen, Guoxing Yang, Zhiwu Lu, Ruihua Song and Xin Gao and has published in prestigious journals such as Nature Communications, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and Neural Information Processing Systems.

In The Last Decade

Nanyi Fei

6 papers receiving 295 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.

Towards artificial general intelligence via a multimodal foundation model

2022 170 citations Nanyi Fei, Zhiwu Lu et al. Nature Communications profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Nanyi Fei China	5	155	141	32	22	14	9	302
Haoyu Lu China	5	123 0.8×	115 0.8×	28 0.9×	22 1.0×	19 1.4×	22	291
Shereen Fouad United Kingdom	10	118 0.8×	73 0.5×	43 1.3×	12 0.5×	13 0.9×	21	235
Oscar Li United States	5	304 2.0×	101 0.7×	35 1.1×	34 1.5×	10 0.7×	14	383
Ruihua Song China	7	144 0.9×	87 0.6×	21 0.7×	23 1.0×	9 0.6×	20	322
Md. Abul Ala Walid Bangladesh	9	113 0.7×	64 0.5×	46 1.4×	6 0.3×	17 1.2×	45	255
А.В. Куракин United States	6	284 1.8×	151 1.1×	23 0.7×	6 0.3×	13 0.9×	8	361
Viktoriia Sharmanska United Kingdom	11	278 1.8×	270 1.9×	42 1.3×	10 0.5×	17 1.2×	18	484
Mantas Mazeika United States	5	384 2.5×	136 1.0×	18 0.6×	19 0.9×	5 0.4×	5	442
Chih‐Kuan Yeh United States	7	348 2.2×	158 1.1×	14 0.4×	14 0.6×	7 0.5×	9	436
Bernd Malle Austria	4	165 1.1×	39 0.3×	20 0.6×	33 1.5×	11 0.8×	4	266

Countries citing papers authored by Nanyi Fei

Since Specialization

Citations

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

Fields of papers citing papers by Nanyi Fei

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nanyi Fei

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

9 of 9 papers shown

1.

Dong, Jing, et al.. (2025). Leveraging Large Vision-Language Model as User Intent-Aware Encoder for Composed Image Retrieval. Proceedings of the AAAI Conference on Artificial Intelligence. 39(7). 7149–7157.

2.

Lu, Haoyu, Yuqi Huo, Mingyu Ding, Nanyi Fei, & Zhiwu Lu. (2023). Cross-modal Contrastive Learning for Generalizable and Efficient Image-text Retrieval. 20(4). 569–582. 11 indexed citations

3.

Yang, Guoxing, et al.. (2023). Text-to-Chinese-painting Method Based on Multi-domain VQGAN. 13(2). 197–219.

4.

Yang, Guoxing, et al.. (2023). DiST-GAN: Distillation-based Semantic Transfer for Text-Guided Face Generation. 840–845.

5.

Fei, Nanyi, Zhiwu Lu, Yizhao Gao, et al.. (2022). Towards artificial general intelligence via a multimodal foundation model. Nature Communications. 13(1). 3094–3094. 170 indexed citations breakdown →

6.

Lu, Haoyu, Nanyi Fei, Yuqi Huo, et al.. (2022). COTS: Collaborative Two-Stream Vision-Language Pre-Training Model for Cross-Modal Retrieval. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 15671–15680. 47 indexed citations

7.

Fei, Nanyi, Zhiwu Lu, Tao Xiang, & Songfang Huang. (2021). MELR: Meta-Learning via Modeling Episode-Level Relationships for Few-Shot Learning. International Conference on Learning Representations. 36 indexed citations

8.

Huo, Yuqi, Mingyu Ding, Haoyu Lu, et al.. (2021). Compressed Video Contrastive Learning. Neural Information Processing Systems. 34. 3 indexed citations

9.

Yang, Guoxing, Nanyi Fei, Mingyu Ding, et al.. (2021). L2M-GAN: Learning to Manipulate Latent Space Semantics for Facial Attribute Editing. 2950–2959. 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.

Explore authors with similar magnitude of impact