Yu Qiao Google Scholar: h-index, Total Citations, and Citation Map
Yu Qiao's h-index is 169 (498 i10-index, 144,078+ total citations across 781+ publications) according to Google Scholar as of October 2026.
Yu Qiao is a researcher affiliated with their institution, specializing in Computer Vision, Pattern Recognition, World Model. Their work has been cited 144,078 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Yu Qiao's Citation Metrics
Bibliometric impact based on 781 indexed publications. Of these, 19 are original research articles — the rest are literature highlights, conference abstracts or theses.
- H-Index
- 169
- i10-Index
- 498
- Total Citations
- 144,078
- Citing Countries
- 97
As of October 2026.
Yu Qiao has an h-index of 169 and 144,078 total citations across 781 publications, with research cited by institutions in 97 countries.
Download Exports (PNG, CSV, Poster)
Free Viewing Yu Qiao's citation map is always free. Pay once to download poster, PNG, and CSV files for offline use or your visa packet.
Global Impact Map
Visualizing the geographic distribution of institutions that have cited your work.
Starting…
Pins will appear here as institutions are resolved — no need to refresh.
Joint face detection and alignment using multitask cascaded convolutional networks
20168,343
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.
1950 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher pioneered enhanced super-resolution via generative adversarial networks, establishing a foundational framework that subsequent work extended to transformer-based and diffusion-based blind image restoration.
The researcher established foundational practices for deep action recognition via Temporal Segment Networks, a framework subsequently expanded into comprehensive multi-modal video understanding benchmarks.
The researcher pioneered multitask cascaded convolutional networks for joint face detection and alignment, establishing a foundational framework that subsequent work extended to robust facial expression recognition under occlusion and uncertainty.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
Related Guides
Learn how to use citation maps for your research and visa applications.
About Yu Qiao's research
Yu Qiao is a researcher working on Computer Vision, Pattern Recognition and World Model. Their work has been cited 144,078 times across 781 publications (h-index 169), according to Google Scholar.
Their most-cited work, “Joint face detection and alignment using multitask cascaded convolutional networks” (2016), has accumulated 8,343 citations. Other influential works include “Esrgan: Enhanced super-resolution generative adversarial networks” (2018) with 7,168 citations and “Temporal segment networks: Towards good practices for deep action recognition” (2016) with 5,617 citations.
Citations of Yu Qiao'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.
