Aming Wu

1.0k total citations
32 papers, 694 citations indexed

About

Aming Wu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Control and Systems Engineering. According to data from OpenAlex, Aming Wu has authored 32 papers receiving a total of 694 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Computer Vision and Pattern Recognition, 24 papers in Artificial Intelligence and 2 papers in Control and Systems Engineering. Recurrent topics in Aming Wu's work include Domain Adaptation and Few-Shot Learning (20 papers), Multimodal Machine Learning Applications (14 papers) and Advanced Neural Network Applications (12 papers). Aming Wu is often cited by papers focused on Domain Adaptation and Few-Shot Learning (20 papers), Multimodal Machine Learning Applications (14 papers) and Advanced Neural Network Applications (12 papers). Aming Wu collaborates with scholars based in China, Australia and Singapore. Aming Wu's co-authors include Yahong Han, Cheng Deng, Yi Yang, Linchao Zhu, Rui Liu, Muli Yang, Yunfeng Shao, Jiang Pin, Zhipeng Wang and Hao Wang and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and IEEE Transactions on Circuits and Systems for Video Technology.

In The Last Decade

Aming Wu

28 papers receiving 684 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Aming Wu China	14	526	427	61	50	44	32	694
Spyros Gidaris France	6	516 1.0×	561 1.3×	120 2.0×	48 1.0×	35 0.8×	13	819
Sivan Harary Israel	10	366 0.7×	307 0.7×	48 0.8×	36 0.7×	60 1.4×	10	508
Jihan Yang Hong Kong	9	529 1.0×	491 1.1×	76 1.2×	68 1.4×	35 0.8×	13	747
Jingru Tan China	6	349 0.7×	335 0.8×	63 1.0×	29 0.6×	67 1.5×	10	598
K J Joseph India	6	380 0.7×	301 0.7×	33 0.5×	38 0.8×	31 0.7×	12	542
Shipeng Yan China	7	357 0.7×	462 1.1×	79 1.3×	21 0.4×	33 0.8×	8	623
Rongyao Fang Hong Kong	5	355 0.7×	247 0.6×	42 0.7×	39 0.8×	33 0.8×	6	542
Massimiliano Mancini Italy	11	292 0.6×	438 1.0×	105 1.7×	27 0.5×	35 0.8×	29	607
Joseph Shtok Israel	8	394 0.7×	295 0.7×	108 1.8×	37 0.7×	64 1.5×	13	598
Sheng Jin China	9	327 0.6×	235 0.6×	37 0.6×	41 0.8×	28 0.6×	16	573

Countries citing papers authored by Aming Wu

Since Specialization

Citations

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

Fields of papers citing papers by Aming Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aming Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Aming Wu. A scholar is included among the top collaborators of Aming Wu 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 Aming Wu. Aming Wu 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

Wang, Yuxuan, et al.. (2025). Reasoning Mamba: Hypergraph-Guided Region Relation Calculating for Weakly Supervised Affordance Grounding. 27618–27627.

Wu, Aming & Cheng Deng. (2025). Percept, Memory, and Imagine: World Feature Simulating for Open-Domain Unknown Object Detection. 4682–4691.

Wang, Yuxuan, Muli Yang, Aming Wu, & Cheng Deng. (2025). Progressive Invariant Causal Feature Learning for Single Domain Generalization. IEEE Transactions on Image Processing. 34. 2694–2706. 1 indexed citations

Wu, Aming, et al.. (2025). Style Evolving along Chain-of-Thought for Unknown-Domain Object Detection. 14225–14234.

Wu, Aming, Cheng Deng, & Wei Liu. (2024). Unsupervised Out-of-Distribution Object Detection via PCA-Driven Dynamic Prototype Enhancement. IEEE Transactions on Image Processing. 33. 2431–2446. 12 indexed citations

Wu, Aming, et al.. (2024). Prompt-Driven Dynamic Object-Centric Learning for Single Domain Generalization. 17606–17615. 10 indexed citations

Yang, Muli, et al.. (2024). Memory-Enhanced Confidence Calibration for Class-Incremental Unsupervised Domain Adaptation. IEEE Transactions on Multimedia. 27. 610–621. 1 indexed citations

Wu, Aming, et al.. (2024). Prototype-Decomposed Knowledge Distillation for Learning Generalized Federated Representation. IEEE Transactions on Multimedia. 26. 10991–11002. 2 indexed citations

Wu, Aming & Cheng Deng. (2023). TIB: Detecting Unknown Objects via Two-Stream Information Bottleneck. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(1). 611–625. 17 indexed citations

10.

Wu, Aming, Da Chen, & Cheng Deng. (2023). Deep Feature Deblurring Diffusion for Detecting Out-of-Distribution Objects. 13335–13345. 8 indexed citations

11.

Wu, Aming & Cheng Deng. (2023). Discriminating Known from Unknown Objects via Structure-Enhanced Recurrent Variational AutoEncoder. 23956–23965. 7 indexed citations

12.

Yang, Muli, et al.. (2022). Divide and Conquer: Compositional Experts for Generalized Novel Class Discovery. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 14248–14257. 19 indexed citations

13.

Wu, Aming & Cheng Deng. (2022). Single-Domain Generalized Object Detection in Urban Scene via Cyclic-Disentangled Self-Distillation. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 837–846. 67 indexed citations

14.

Wu, Aming, et al.. (2021). Generalized and Discriminative Few-Shot Object Detection via SVD-Dictionary Enhancement. Neural Information Processing Systems. 34. 14 indexed citations

15.

Wu, Aming, Rui Liu, Yahong Han, Linchao Zhu, & Yi Yang. (2021). Vector-Decomposed Disentanglement for Domain-Invariant Object Detection. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 9322–9331. 93 indexed citations

16.

Li, Liang, Aming Wu, & Yahong Han. (2021). Graph-in-Graph Contrastive Learning for Semi-Supervised Adaptation. 9. 1–6. 1 indexed citations

17.

Wu, Aming, Yahong Han, Zhou Zhao, & Yi Yang. (2020). Hierarchical Memory Decoder for Visual Narrating. IEEE Transactions on Circuits and Systems for Video Technology. 31(6). 2438–2449. 11 indexed citations

18.

Pin, Jiang, et al.. (2020). Bidirectional Adversarial Training for Semi-Supervised Domain Adaptation. 934–940. 56 indexed citations

19.

Wu, Aming, Yahong Han, Yi Yang, Qinghua Hu, & Fei Wu. (2019). Convolutional Reconstruction-to-Sequence for Video Captioning. IEEE Transactions on Circuits and Systems for Video Technology. 30(11). 4299–4308. 29 indexed citations

20.

Wu, Aming, Linchao Zhu, Yahong Han, & Yi Yang. (2019). Connective Cognition Network for Directional Visual Commonsense Reasoning. Neural Information Processing Systems. 32. 5669–5679. 14 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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