Richard Zhang

24.8k total citations · 5 hit papers
51 papers, 3.0k citations indexed

About

Richard Zhang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Richard Zhang has authored 51 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Computer Vision and Pattern Recognition, 7 papers in Artificial Intelligence and 6 papers in Electrical and Electronic Engineering. Recurrent topics in Richard Zhang's work include Generative Adversarial Networks and Image Synthesis (24 papers), Advanced Image Processing Techniques (8 papers) and Advanced Vision and Imaging (7 papers). Richard Zhang is often cited by papers focused on Generative Adversarial Networks and Image Synthesis (24 papers), Advanced Image Processing Techniques (8 papers) and Advanced Vision and Imaging (7 papers). Richard Zhang collaborates with scholars based in United States, Canada and United Kingdom. Richard Zhang's co-authors include Alexei A. Efros, Jun-Yan Zhu, Eli Shechtman, Oliver Wang, Phillip Isola, Sheng-Yu Wang, Andrew Owens, Nupur Kumari, Bingliang Zhang and Gaurav Parmar and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Scientific Reports and Annals of the Rheumatic Diseases.

In The Last Decade

Richard Zhang

49 papers receiving 2.9k citations

Hit Papers

5 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.

CNN-Generated Images Are Surprisingly Easy to Spot… for Now

2020 541 citations Oliver Wang, Richard Zhang et al. profile →
Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction

2017 344 citations Richard Zhang, Phillip Isola et al. profile →
Multi-Concept Customization of Text-to-Image Diffusion

2023 273 citations Richard Zhang, Eli Shechtman et al. profile →
Scaling up GANs for Text-to-Image Synthesis

2023 186 citations Minguk Kang, Jun-Yan Zhu et al. profile →
On Aliased Resizing and Surprising Subtleties in GAN Evaluation

2022 141 citations Richard Zhang, Jun-Yan Zhu et al. profile →

Peers

Countries citing papers authored by Richard Zhang

Since Specialization

Citations

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

Fields of papers citing papers by Richard Zhang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Richard Zhang

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work	Indexed citations
1	VideoGigaGAN: Towards Detail-rich Video Super-Resolution 2025 ·(unknown), Taesung Park, Richard Zhang, Yang Zhou, Eli Shechtman, Feng Liu, Jia‐Bin Huang, (unknown)	1
2	Optimal graph representations and neural networks for multichannel time series data in seizure phase classification 2025 ·Scientific Reports ·(unknown), Richard Zhang, Milad Lankarany	0
3	By-Software Branch Prediction in Loops 2023 ·IEEE Computer Architecture Letters ·Maziar Goudarzi, Reza Azimi, (unknown), (unknown), Richard Zhang, (unknown), (unknown), Yuqi Yang	2
4	Scaling up GANs for Text-to-Image Synthesis breakdown → 2023 ·Minguk Kang, Jun-Yan Zhu, Richard Zhang, Jaesik Park, Eli Shechtman, Sylvain Paris, Taesung Park	186
5	Temporal quality degradation in AI models 2022 ·Scientific Reports ·(unknown), Andrew J. Sharp, Richard Zhang, Trang Nguyen, (unknown), Oleg S. Pianykh	79
6	Contrastive Feature Loss for Image Prediction 2021 ·Alex Andonian, Taesung Park, Bryan Russell, Phillip Isola, Jun-Yan Zhu, Richard Zhang	16
7	Few-shot Image Generation via Cross-domain Correspondence 2021 ·Utkarsh Ojha, Yijun Li, Jingwan Lu, Alexei A. Efros, Yong Jae Lee, Eli Shechtman, Richard Zhang	139
8	Random Hypervolume Scalarizations for Provable Multi-Objective Black Box Optimization 2020 ·International Conference on Machine Learning ·Richard Zhang, Daniel Golovin	4
9	Swapping Autoencoder for Deep Image Manipulation 2020 ·Neural Information Processing Systems ·Taesung Park, Jun-Yan Zhu, Oliver Wang, Jingwan Lu, Eli Shechtman, Alexei A. Efros, Richard Zhang	13
10	Image Synthesis for Self-Supervised Visual Representation Learning 2018 ·eScholarship (California Digital Library) ·Richard Zhang	1
11	Multimodal Image-to-Image Translation by Enforcing Bi-Cycle Consistency 2017 ·Neural Information Processing Systems ·Jun-Yan Zhu, Richard Zhang, Deepak Pathak, Trevor Darrell, Oliver Wang, Eli Shechtman, Alexei A. Efros	20
12	Toward Multimodal Image-to-Image Translation 2017 ·arXiv (Cornell University) ·Jun Zhu, Richard Zhang, Deepak Pathak, Trevor Darrell, Alexei A. Efros, Oliver Wang, Eli Shechtman	203
13	Incremental forest: a DSL for efficiently managing filestores 2016 ·ACM SIGPLAN Notices ·(unknown), Richard Zhang, (unknown), Kathleen Fisher, Nate Foster	0
14	RadMAP: The Radiological Multi-sensor Analysis Platform 2016 ·Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment ·Mark S. Bandstra, (unknown), E. Brubaker, (unknown), R.J. Cooper, (unknown), J. Davis, Tenzing H. Y. Joshi, (unknown), (unknown), (unknown), Michael Quinlan, Brian J. Quiter, (unknown), Avideh Zakhor, Richard Zhang, K. Vetter	26
15	Sensor fusion for semantic segmentation of urban scenes 2015 ·Richard Zhang, (unknown), K. Vetter, Avideh Zakhor	79
16	Automatic identification of window regions on indoor point clouds using LiDAR and cameras 2014 ·Richard Zhang, Avideh Zakhor	15
17	Safety of celecoxib compared with placebo and non-selective NSAIDs: cumulative meta-analysis of 89 randomized controlled trials 2013 ·Expert Opinion on Drug Safety ·Margaret Noyes Essex, Richard Zhang, Manuela Berger, (unknown), Peter W. Park	32
18	Test-bench for very high power variable frequency drives working under constrained grid conditions 2013 ·Stefan Schröder, Jie Shen, Fan Zhang, Kunlun Chen, (unknown), Richard Zhang	11
19	A go-cart as an electric vehicle for undergraduate teaching and assessment 2010 ·Australasian Universities Power Engineering Conference ·(unknown), R. Duke, Richard Zhang, Paul Gaynor, (unknown)	3
20	Rates of Cognitive Change in Alzheimer Disease 2009 ·Alzheimer Disease & Associated Disorders ·Roy Jones, Elias Schwam, David Wilkinson, Gunhild Waldemar, Howard Feldman, Richard Zhang, Kenneth S. Albert, Rachel Schindler	20

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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