Kangle Deng: h-index, Total Citations, and Citation Map
Kangle Deng's h-index is 9 (9 i10-index, 1,712+ total citations across 17+ publications) according to Google Scholar as of June 2026. Kangle Deng is affiliated with Roblox.
Kangle Deng is a researcher affiliated with Roblox, specializing in Computer Vision. Their work has been cited 1,712 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Kangle Deng's Citation Metrics
Bibliometric impact based on 17 indexed publications.
- H-Index
- 9
- i10-Index
- 9
- Total Citations
- 1,712
- Citing Countries
- 53
As of June 2026.
Kangle Deng has an h-index of 9 and 1,712 total citations across 17 publications, with research cited by institutions in 53 countries.
Download Exports (PNG, CSV, Poster)
Free Viewing Kangle Deng'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.
Depth-supervised nerf: Fewer views and faster training for free
20221,378
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.
50 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher advanced neural radiance fields by introducing depth supervision for efficient training and extending the framework to conditional synthesis and deformable scene reconstruction.
The researcher advanced fast relightable mesh texturing and physically stable generative modeling, establishing a foundational framework widely adopted by independent scholars in computer graphics.
The researcher developed IRC-GAN, an introspective recurrent convolutional framework that advanced text-to-video generation by integrating self-reflective mechanisms to improve temporal coherence and visual fidelity in synthesized video sequences.
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 Kangle Deng's research
Kangle Deng is a researcher in Computer Vision at Roblox. Their work has been cited 1,712 times across 17 publications (h-index 9), according to Google Scholar.
Their most-cited work, “Depth-supervised nerf: Fewer views and faster training for free” (2022), has accumulated 1,378 citations. Other influential works include “IRC-GAN: Introspective Recurrent Convolutional GAN for Text-to-video Generation.” (2019) with 72 citations and “Flashtex: Fast relightable mesh texturing with lightcontrolnet” (2024) with 63 citations.
Citations of Kangle Deng's research come primarily from China, United States and Germany, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.











