Hongsheng Li: h-index, Total Citations, and Citation Map
Hongsheng Li's h-index is 134 (377 i10-index, 84,317+ total citations across 481+ publications) according to Google Scholar as of July 2026. Hongsheng Li is affiliated with The Chinese University of Hong Kong.
Hongsheng Li is a researcher affiliated with The Chinese University of Hong Kong, specializing in Multimodal Learning, Embodied AI, Computer Vision. Their work has been cited 84,317 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Hongsheng Li's Citation Metrics
Bibliometric impact based on 481 indexed publications.
- H-Index
- 134
- i10-Index
- 377
- Total Citations
- 84,317
- Citing Countries
- 58
As of July 2026.
Hongsheng Li has an h-index of 134 and 84,317 total citations across 481 publications, with research cited by institutions in 58 countries.
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Global Impact Map
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StackGAN: Text to photo-realistic image synthesis with stacked generative adversarial networks
20174,382
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.
1149 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher pioneered training-free adaptation methods for vision-language models, extending this framework to efficient fine-tuning of large language and visual instruction models.
The researcher developed CLIP-Adapter, a feature adapter method that enhances vision-language models, as evidenced by its publication in IJCV and over 2,200 citations.
The researcher developed StackGAN, a stacked generative adversarial network architecture that enables text-to-photo-realistic image synthesis, establishing a foundational method for high-fidelity visual generation.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Hongsheng Li's research
Hongsheng Li is a researcher in Multimodal Learning, Embodied AI and Computer Vision at The Chinese University of Hong Kong. Their work has been cited 84,317 times across 481 publications (h-index 134), according to Google Scholar.
Their most-cited work, “StackGAN: Text to photo-realistic image synthesis with stacked generative adversarial networks” (2017), has accumulated 4,382 citations. Other influential works include “PointRCNN: 3D object proposal generation and detection from point cloud” (2019) with 3,982 citations and “PV-RCNN: Point-voxel feature set abstraction for 3D object detection” (2020) with 3,144 citations.
Citations of Hongsheng Li's research come primarily from China, United States and Singapore, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
