Weidi Xie

10.2k total citations · 4 hit papers
62 papers, 4.0k citations indexed

About

Weidi Xie is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Weidi Xie has authored 62 papers receiving a total of 4.0k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Computer Vision and Pattern Recognition, 27 papers in Artificial Intelligence and 11 papers in Signal Processing. Recurrent topics in Weidi Xie's work include Advanced Neural Network Applications (19 papers), Domain Adaptation and Few-Shot Learning (18 papers) and Multimodal Machine Learning Applications (15 papers). Weidi Xie is often cited by papers focused on Advanced Neural Network Applications (19 papers), Domain Adaptation and Few-Shot Learning (18 papers) and Multimodal Machine Learning Applications (15 papers). Weidi Xie collaborates with scholars based in United Kingdom, China and United States. Weidi Xie's co-authors include Andrew Zisserman, Omkar Parkhi, Qiong Cao, Li Shen, Arsha Nagrani, J. Alison Noble, Joon Son Chung, Honglie Chen, Andrea Vedaldi and Erika Lu and has published in prestigious journals such as NeuroImage, ACM Transactions on Graphics and International Journal of Computer Vision.

In The Last Decade

Weidi Xie

61 papers receiving 3.9k citations

Hit Papers

VGGFace2: A Dataset for Recognising Faces across Pose and... 2018 2026 2020 2023 2018 2019 2020 2024 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Weidi Xie United Kingdom 24 2.5k 1.4k 1.4k 269 181 62 4.0k
Omkar Parkhi United Kingdom 13 5.1k 2.0× 1.2k 0.9× 1.9k 1.4× 129 0.5× 512 2.8× 19 6.0k
Mayank Vatsa India 47 4.8k 1.9× 981 0.7× 3.9k 2.9× 191 0.7× 77 0.4× 307 6.8k
Barret Zoph United States 12 2.0k 0.8× 3.3k 2.5× 1.5k 1.1× 197 0.7× 137 0.8× 20 4.9k
Erik Learned-Miller United States 26 3.6k 1.4× 846 0.6× 545 0.4× 158 0.6× 53 0.3× 95 4.4k
Tal Hassner Israel 30 5.1k 2.0× 1.1k 0.8× 1.5k 1.1× 80 0.3× 329 1.8× 95 5.7k
Mohamed Abdel-Mottaleb United States 33 3.0k 1.2× 597 0.4× 902 0.7× 561 2.1× 152 0.8× 132 4.5k
Yaniv Taigman Israel 10 4.0k 1.6× 929 0.7× 1.4k 1.1× 120 0.4× 164 0.9× 13 4.9k
Ming Dong United States 23 1.1k 0.4× 760 0.6× 549 0.4× 351 1.3× 551 3.0× 97 2.5k
Marcin Grzegorzek Germany 31 1.7k 0.7× 1.3k 1.0× 212 0.2× 727 2.7× 90 0.5× 233 3.8k

Countries citing papers authored by Weidi Xie

Since Specialization
Citations

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

Fields of papers citing papers by Weidi Xie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Weidi Xie

This figure shows the co-authorship network connecting the top 25 collaborators of Weidi Xie. A scholar is included among the top collaborators of Weidi Xie 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 Weidi Xie. Weidi Xie 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, Yao, Chaoyi Wu, Xiaoman Zhang, et al.. (2025). Large-vocabulary segmentation for medical images with text prompts. npj Digital Medicine. 8(1). 566–566. 1 indexed citations
2.
Chen, Keyan, et al.. (2024). OV-DAR: Open-Vocabulary Object Detection and Attributes Recognition. International Journal of Computer Vision. 132(11). 5387–5409. 1 indexed citations
3.
Xie, Weidi, et al.. (2024). EchoSight: Advancing Visual-Language Models with Wiki Knowledge. 1538–1551. 2 indexed citations
4.
Zheng, Chuanxia, et al.. (2024). Amodal Ground Truth and Completion in the Wild. 28003–28013. 8 indexed citations
5.
Haak, Monique C., et al.. (2024). Sensorless volumetric reconstruction of fetal brain freehand ultrasound scans with deep implicit representation. Medical Image Analysis. 94. 103147–103147. 4 indexed citations
6.
Wang, Yu, et al.. (2024). Annotation-free Audio-Visual Segmentation. 5592–5602. 12 indexed citations
7.
Li, Ziyi, et al.. (2023). Open-vocabulary Object Segmentation with Diffusion Models. 7633–7642. 18 indexed citations
8.
Shin, Gyungin, Samuel Albanie, & Weidi Xie. (2022). Unsupervised Salient Object Detection with Spectral Cluster Voting. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). 3970–3979. 36 indexed citations
9.
Chen, Honglie, Weidi Xie, Andrea Vedaldi, & Andrew Zisserman. (2020). Vggsound: A Large-Scale Audio-Visual Dataset. Oxford University Research Archive (ORA) (University of Oxford). 721–725. 234 indexed citations breakdown →
10.
Xie, Weidi, et al.. (2020). Low-Memory CNNs Enabling Real-Time Ultrasound Segmentation Towards Mobile Deployment. IEEE Journal of Biomedical and Health Informatics. 24(4). 1059–1069. 24 indexed citations
11.
Han, Tengda, Weidi Xie, & Andrew Zisserman. (2020). Self-supervised Co-Training for Video Representation Learning. Neural Information Processing Systems. 33. 5679–5690. 5 indexed citations
12.
Lai, Zihang, Erika Lu, & Weidi Xie. (2020). MAST: A Memory-Augmented Self-Supervised Tracker. 6478–6487. 94 indexed citations
13.
Xu, Dan, Weidi Xie, & Andrew Zisserman. (2019). Geometry-Aware Video Object Detection for Static Cameras.. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 294. 1 indexed citations
14.
Lai, Zihang & Weidi Xie. (2019). Self-supervised Video Representation Learning for Correspondence Flow.. British Machine Vision Conference. 299. 1 indexed citations
15.
Namburete, Ana I. L., Weidi Xie, Mohammad Yaqub, Andrew Zisserman, & J. Alison Noble. (2018). Fully-automated alignment of 3D fetal brain ultrasound to a canonical reference space using multi-task learning. Medical Image Analysis. 46. 1–14. 57 indexed citations
16.
Xie, Weidi & Andrew Zisserman. (2018). Multicolumn Networks for Face Recognition. Oxford University Research Archive (ORA) (University of Oxford). 111. 11 indexed citations
17.
Vigneault, Davis M., Weidi Xie, Carolyn Y. Ho, David A. Bluemke, & J. Alison Noble. (2018). Ω-Net (Omega-Net): Fully automatic, multi-view cardiac MR detection, orientation, and segmentation with deep neural networks. Medical Image Analysis. 48. 95–106. 95 indexed citations
18.
Huang, Ruobing, Weidi Xie, & J. Alison Noble. (2018). VP-Nets : Efficient automatic localization of key brain structures in 3D fetal neurosonography. Medical Image Analysis. 47. 127–139. 34 indexed citations
19.
Xie, Weidi, Yin Cheong Wong, & Sai Wah Tsao. (2000). Correlation of increased apoptosis and proliferation with development of prostatic intraepithelial neoplasia (PIN) in ventral prostate of the noble rat. The Prostate. 44(1). 31–39. 38 indexed citations
20.
Wong, Yi‐Lee, Weidi Xie, & Sai Wah Tsao. (2000). Structural changes and alteration in expression of TGF-?1 and its receptors in prostatic intraepithelial neoplasia (PIN) in the ventral prostate of noble rats. The Prostate. 45(4). 289–298. 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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