Huan Ling

2.5k total citations · 1 hit paper
33 papers, 1.1k citations indexed

About

Huan Ling is a scholar working on Computer Vision and Pattern Recognition, Materials Chemistry and Radiation. According to data from OpenAlex, Huan Ling has authored 33 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Vision and Pattern Recognition, 8 papers in Materials Chemistry and 5 papers in Radiation. Recurrent topics in Huan Ling's work include Generative Adversarial Networks and Image Synthesis (6 papers), Advanced Neural Network Applications (6 papers) and Luminescence Properties of Advanced Materials (6 papers). Huan Ling is often cited by papers focused on Generative Adversarial Networks and Image Synthesis (6 papers), Advanced Neural Network Applications (6 papers) and Luminescence Properties of Advanced Materials (6 papers). Huan Ling collaborates with scholars based in China, Canada and United States. Huan Ling's co-authors include Sanja Fidler, Amlan Kar, David Acuna, Jun Gao, Karsten Kreis, Seung Wook Kim, Robin Rombach, Tim Dockhorn, Andreas Blattmann and Wenzheng Chen and has published in prestigious journals such as Advanced Materials, Nature Communications and Nano Letters.

In The Last Decade

Huan Ling

29 papers receiving 1.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Align Your Latents: High-Resolution Video Synthesis with Latent Diffusion Models

2023 249 citations Huan Ling, Seung Wook Kim et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Huan Ling China	12	740	209	94	90	89	33	1.1k
Zunlei Feng China	14	762 1.0×	281 1.3×	30 0.3×	113 1.3×	84 0.9×	83	1.3k
Sergey Ablameyko Belarus	12	568 0.8×	207 1.0×	39 0.4×	18 0.2×	92 1.0×	129	955
Xiangtai Li China	18	936 1.3×	347 1.7×	61 0.6×	13 0.1×	263 3.0×	58	1.6k
Zijian He China	14	486 0.7×	278 1.3×	21 0.2×	34 0.4×	54 0.6×	41	761
Viacheslav Voronin Russia	13	423 0.6×	83 0.4×	29 0.3×	33 0.4×	118 1.3×	171	762
Yihao Liu China	14	948 1.3×	83 0.4×	43 0.5×	23 0.3×	361 4.1×	59	1.3k
Jun Sun China	20	720 1.0×	59 0.3×	24 0.3×	144 1.6×	81 0.9×	83	1.2k
Zhilong Zhang China	7	274 0.4×	199 1.0×	18 0.2×	44 0.5×	47 0.5×	29	782

Countries citing papers authored by Huan Ling

Since Specialization

Citations

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

Fields of papers citing papers by Huan Ling

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Huan Ling

This figure shows the co-authorship network connecting the top 25 collaborators of Huan Ling. A scholar is included among the top collaborators of Huan Ling 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 Huan Ling. Huan Ling is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

1.

Zhang, Yanxin, Rongrong Wen, Wenrui Zhang, et al.. (2025). Enhanced Single‐Particle Upconversion Imaging via Energy Migration Boosting. Advanced Science. 12(43). e10624–e10624.

2.

Ling, Huan, Wenrui Zhang, Yunxiang Zhang, Jie Shen, & Qian Liu. (2025). Lanthanide‐Doped Upconversion Nanoparticles for Single‐Particle Imaging. ChemBioChem. 26(11). e202400942–e202400942. 1 indexed citations

3.

Shen, Tianchang, Jiahui Huang, Huan Ling, et al.. (2025). Gen3C: 3D-Informed World-Consistent Video Generation with Precise Camera Control. 6121–6132. 2 indexed citations

4.

Gojčič, Žan, Huan Ling, Jacob Munkberg, et al.. (2025). DiffusionRenderer: Neural Inverse and Forward Rendering with Video Diffusion Models. 26069–26080.

5.

Ling, Huan, Jinyang Liu, Fan Ding, et al.. (2025). Long-Term Single-Particle Tracking of Membrane Proteins Enabled by Upconversion Alkaline-Earth Nanoprobes. Nano Letters. 25(31). 11819–11828.

6.

Wu, Jay Zhangjie, Yuxuan Zhang, Mike Zheng Shou, et al.. (2025). Difix3D+: Improving 3D Reconstructions with Single-Step Diffusion Models. 26024–26035.

7.

Qiu, Xiaochen, Huan Ling, Jialing Hu, et al.. (2025). Sub-10 nm upconversion nanocrystals for long-term single-particle tracking. Nature Communications. 16(1). 9408–9408. 2 indexed citations

8.

Ling, Huan, Rongrong Wen, Jialing Hu, et al.. (2024). Effect of Surface Modification on the Luminescence of Individual Upconversion Nanoparticles. Small. 20(26). e2309035–e2309035. 29 indexed citations

9.

Xu, Chenfeng, Huan Ling, Sanja Fidler, & Or Litany. (2024). 3DiffTection: 3D Object Detection with Geometry-Aware Diffusion Features. 10617–10627. 2 indexed citations

10.

Zhao, Fei, Jialing Hu, Jinyang Liu, et al.. (2023). Boosting Dye‐Sensitized Luminescence by Enhanced Short‐Range Triplet Energy Transfer. Advanced Materials. 35(51). e2304907–e2304907. 25 indexed citations

11.

Li, Daiqing, Huan Ling, Seung Wook Kim, et al.. (2022). BigDatasetGAN: Synthesizing ImageNet with Pixel-wise Annotations. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 21298–21308. 38 indexed citations

12.

Zhang, Yuxuan, Huan Ling, Jun Gao, et al.. (2021). DatasetGAN: Efficient Labeled Data Factory with Minimal Human Effort. 10140–10150. 132 indexed citations

13.

Penn, Gerald, et al.. (2021). Structural Realization with GGNNs. 115–124. 1 indexed citations

14.

Ling, Huan, Karsten Kreis, Daiqing Li, et al.. (2021). EditGAN: High-Precision Semantic Image Editing. arXiv (Cornell University). 1 indexed citations

15.

Ling, Huan, David Acuna, Karsten Kreis, Seung Wook Kim, & Sanja Fidler. (2020). Variational Amodal Object Completion. Neural Information Processing Systems. 33. 16246–16257. 14 indexed citations

16.

Chen, Wenzheng, Huan Ling, Jun Gao, et al.. (2019). Learning to Predict 3D Objects with an Interpolation-based Differentiable Renderer. arXiv (Cornell University). 32. 9605–9616. 33 indexed citations

17.

Huang, Fangfang, Huan Ling, Jiao Li, et al.. (2019). Synthesis, bioactivities and 3D-QSAR of novel avermectin B2a aglycon derivatives. Chinese Chemical Letters. 31(1). 141–144. 7 indexed citations

18.

Acuna, David, Huan Ling, Amlan Kar, & Sanja Fidler. (2018). Efficient Interactive Annotation of Segmentation Datasets with Polygon-RNN++. 859–868. 252 indexed citations

19.

Ling, Huan & Sanja Fidler. (2017). Teaching Machines to Describe Images with Natural Language Feedback. Neural Information Processing Systems. 30. 5068–5078. 17 indexed citations

20.

Ling, Huan. (2012). The Survey and Analysis of Disabled Sports' Development in Zhejiang Province. 1 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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