Xiaojuan Qi: h-index, Total Citations, and Citation Map
Xiaojuan Qi's h-index is 20 (20 i10-index, 49,747+ total citations across 20+ publications) according to Google Scholar as of July 2026. Xiaojuan Qi is affiliated with Associate Professor, The University of Hong Kong.
Xiaojuan Qi is a researcher affiliated with Associate Professor, The University of Hong Kong, specializing in various fields. Their work has been cited 49,747 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Xiaojuan Qi's Citation Metrics
Bibliometric impact based on 20 indexed publications.
- H-Index
- 20
- i10-Index
- 20
- Total Citations
- 49,747
- Citing Countries
- 64
As of July 2026.
Xiaojuan Qi has an h-index of 20 and 49,747 total citations across 20 publications, with research cited by institutions in 64 countries.
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Global Impact Map
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Pyramid Scene Parsing Network
201715,177
Top Citing Countries
Top Citing Institutions
Visa Evidence Package
Views and exports tuned for EB-1A, O-1A, and EB-2 NIW petitions. Sustained acclaim, geographic reach, and independent-citation filtering are the strongest evidence categories immigration adjudicators look for.
Significant Contributions
Auto-detected research lines — a seminal paper and the follow-up work building on it. Review and edit before using in a petition. Each Free PDF opens in a new tab — EB-1A organises this into the structure USCIS applies to Criterion 5 of 8 CFR § 204.5(h)(3)(v); EB-1B re-frames it under § 204.5(i)(3) (outstanding researcher); NIW presents it under prong 2 of Matter of Dhanasar.
11 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher developed the Pyramid Scene Parsing Network, a seminal architecture for scene parsing that has achieved widespread adoption and high citation impact in the computer vision community.
The researcher developed ST3D, a self-training framework for unsupervised domain adaptation in 3D object detection, establishing a foundational approach for transferring detection models across domains without labeled target data.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Xiaojuan Qi's research
Xiaojuan Qi is a researcher at Associate Professor, The University of Hong Kong. Their work has been cited 49,747 times across 20 publications (h-index 20), according to Google Scholar.
Their most-cited work, “Pyramid Scene Parsing Network” (2017), has accumulated 15,177 citations. Other influential works include “H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation From CT Volumes” (2018) with 2,398 citations and “ICNet for Real-Time Semantic Segmentation on High-Resolution Images” (2018) with 1,559 citations.
Citations of Xiaojuan Qi's research come primarily from China, United States and United Kingdom, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
