Anjul Patney
Bio
I lead a product-oriented research team in AI for gaming at NVIDIA. Our research is centered around AI, computer graphics, and visual perception. My work has led to advances in deep-learning for real-time graphics (co-developed DLSS 4, Project G-Assist, RTX HDR, RTX Dynamic Vibrance, DLSS 1.0), perceptual metrics for image quality (FovVideoVDP), foveated rendering for VR, and VR redirected walking.
Previously, I was a Research Scientist at Facebook Reality Labs (2019-2021) and a Senior Research Scientist in Real-Time Rendering at NVIDIA (2013-2019). I received my Ph.D. from UC Davis in 2013, and my B.Tech. from IIT Delhi in 2007.
I try to track SIGGRAPH Trends.
2025
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Detection of artifacts in clean and corrupted video pairs is influenced by artifact type
and presentation modality Niall L. Williams, Anatolii Evdokimov, Budmonde Duinkharjav, Anjul Patney, Qi Sun, Jae-Hyun Jung, Ruth Rosenholtz Journal of Vision 2025 (VSS) JOV |
2023
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The Shortest Route Is Not Always the Fastest: Probability-Modeled Stereoscopic Eye Movement Completion Time in VR SIGGRAPH Asia Project Preprint |
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Online Overexposed Pixels Hallucination in Videos with Adaptive Reference Frame Selection Yazhou Xing, Amrita Mazumdar, Anjul Patney, Chao Liu, Hongxu Yin, Qifeng Chen, Jan Kautz, Iuri Frosio arXiv:2308.15462 |
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Power, Performance, and Image Quality Tradeoffs in Foveated Rendering Rahul Singh, Muhammad Huzaifa, Jeffrey Liu, Anjul Patney, Hashim Sharif, Yifan Zhao, Sarita Adve IEEE Conference on Virtual Reality IEEE Preprint |
2022
2021
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FovVideoVDP: A Visible Difference Predictor for Wide Field-of-view Video Rafał K. Mantiuk, Gyorgy Denes, Alexandre Chapiro, Anton Kaplanyan, Gizem Rufo, Romain Bachy, Trisha Lian, and Anjul Patney SIGGRAPH Project Preprint Presentation Code |
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FovDots: Foveated rendering dataset Gyorgy Denes, Anjul Patney, Gizem Rufo, Alexandre Chapiro, Anton Kaplanyan, Romain Bachy, Trisha Lian, Rafal Mantiuk Dataset |
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Subjective and Objective Quality Assessment of 2D and 3D Foveated Video Compression in Virtual Reality Yize Jin, Meixu Chen, Todd Goodall, Anjul Patney, and Alan C. Bovik IEEE Transactions on Image Processing Dataset IEEE |
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A foveated video quality assessment model using space-variant natural scene statistics Yize Jin, Todd Goodall, Anjul Patney, Richard Webb, Alan C. Bovik IEEE International Conference on Image Processing IEEE Preprint |
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Evaluating Foveated Video Quality Using Entropic Differencing Yize Jin, Anjul Patney, Alan C. Bovik Picture Coding Symposium IEEE |
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MOVI-Codec: Deep Video Compression without Motion Meixu Chen, Todd Goodall, Anjul Patney, Alan C. Bovik Picture Coding Symposium IEEE |
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FOVQA: Blind Foveated Video Quality Assessment Yize Jin, Anjul Patney, Richard Webb, Alan C. Bovik arXiv:2106.13328 Preprint |
2020
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Semi-Supervised StyleGAN for Disentanglement Learning Weili Nie, Tero Karras, Animesh Garg, Shoubhik Debnath, Anjul Patney, Ankit B. Patel and Anima Anandkumar ICML Project arXiv Slides Data |
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Neural Temporal Adaptive Sampling and Denoising Jon Hasselgren, Jacob Munkberg, Marco Salvi, Anjul Patney and Aaron Lefohn Eurographics Project Preprint Video Recording |
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State of the Art in Perceptual VR Displays Gordon Wetzstein, Anjul Patney and Qi Sun Book Chapter in Real VR – Immersive Digital Reality Springer |
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Redirected Walking in VR Qi Sun, Anjul Patney and Frank Steinicke Book Chapter in Real VR – Immersive Digital Reality Springer |
2019
2018
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Towards Virtual Reality Infinite Walking: Dynamic Saccadic Redirection Qi Sun, Anjul Patney, Li-Yi Wei, Omer Shapira, Jingwan Lu, Paul Asente, Suwen Zhu, Morgan McGuire, David Luebke and Arie Kaufman ACM Transactions on Graphics (SIGGRAPH) Project Preprint Fast Forward Video Two-minute Papers GTC Demo |
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Detecting Aliasing Artifacts in Image Sequences Using Deep Neural Networks Anjul Patney and Aaron Lefohn High-Performance Graphics ACM Slides |
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Spoke-Darts for High-Dimensional Blue Noise Sampling Scott A. Mitchell, Mohamed S. Ebeida, Muhammad A. Awad, Chonhyon Park, Anjul Patney, Ahmad A. Rushdi, Laura P. Swiler, Dinesh Manocha and Li-Yi Wei ACM Transactions on Graphics Preprint Video Code |
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Applications of Vision Science to Virtual and Augmented Reality Anjul Patney, Marina Zannoli, Joohwan Kim, Robert Konrad, Frank Steinicke, Martin S. Banks ACM SIGGRAPH 2018 Course Course Page |
2017
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Latency Requirements for Foveated Rendering in Virtual RealityBest Paper Award Rachel Albert, Joohwan Kim, Anjul Patney and David Luebke ACM Transactions on Applied Perception (Symposium on Applied Perception 2017) Project Preprint |
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Spatiotemporal Variance-Guided Filtering: Real-Time Reconstruction for Path-Traced Global IlluminationWolfgang Straßer Best Paper Award Christoph Schied, Anton Kaplanyan, Chris Wyman, Anjul Patney, Chakravarty R. Alla Chaitanya, John Burgess, Shiqiu Liu, Carsten Dachsbacher, Aaron Lefohn, and Marco Salvi High-Performance Graphics 2017 Project Preprint Video |
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Applications of Visual Perception to Virtual Reality Rendering Anjul Patney, Marina Zannoli, George-Alex Koulieris, Joohwan Kim, Gordon Wetzstein, Frank Steinicke ACM SIGGRAPH 2017 Course Course Page |
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Perceptual Insights into Foveated Virtual Reality Anjul Patney NVIDIA GTC 2017 Talk: Slides Recording SIGGRAPH 2017 Recap: Slides |
2016
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Towards Foveated Rendering for Gaze-Tracked Virtual Reality Anjul Patney, Marco Salvi, Joohwan Kim, Anton Kaplanyan, Chris Wyman, Nir Benty, David Luebke, Aaron Lefohn ACM Transactions on Graphics (SIGGRAPH Asia) Project Preprint Supplementary Material Slides Fast Forward |
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Perceptually-Based Foveated Virtual RealityLaval Virtual Award Anjul Patney, Joohwan Kim, Marco Salvi, Anton Kaplanyan, Chris Wyman, Nir Benty, Aaron Lefohn, David Luebke ACM SIGGRAPH 2016 Emerging Technologies Project Abstract Video |
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Filtering Distributions of Normals for Shading AntialiasingWolfgang Straßer Best Paper Award Anton Kaplanyan, Stephen Hill, Anjul Patney, Aaron Lefohn High-Performance Graphics, June 2016 Project Preprint Video |
2015
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Piko: A Framework for Authoring Programmable Graphics Pipelines Anjul Patney, Stanley Tzeng, Kerry A. Seitz, Jr., and John D. Owens ACM Transactions on Graphics (SIGGRAPH) ACM Preprint arXiv:1404.6293 Slides |
2014
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Exercises in High-Dimensional Sampling: Maximal Poisson-disk Sampling and k-d Darts Mohamed Ebeida, Scott Mitchell, Anjul Patney, Andrew Davidson, Stanley Tzeng, Muhammad Awad, Ahmed Mahmoud and John D. Owens Topological and Statistical Methods for Complex Data -- Tackling Large-Scale, High-Dimensional, and Multivariate Data Sets, June 2014 Springer |
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k-d Darts: Sampling by k-Dimensional Flat Searches Mohamed S. Ebeida, Anjul Patney, Scott A. Mitchell, Keith R. Dalbey, Andrew A. Davidson, and John D. Owens ACM Transactions on Graphics ACM arXiv |
2013
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Programmable Graphics Pipelines Anjul Patney Ph.D. Dissertation, University of California at Davis |
2012
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High-Quality Parallel Depth-of-Field Using Line Samples Stanley Tzeng, Anjul Patney, Andrew A. Davidson, Mohamed S. Ebeida, Scott A. Mitchell, and John D. Owens High-Performance Graphics, June 2012 ACM Slides |
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A Simple Algorithm for Maximal Poisson-Disk Sampling in High Dimensions Mohamed S. Ebeida, Scott A. Mitchell, Anjul Patney, Andrew A. Davidson, and John D. Owens Computer Graphics Forum ACM Slides Fast-Forward |
2011
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Efficient and Good Delaunay Meshes From Random Points Mohamed S. Ebeida, Scott A. Mitchell, Andrew A. Davidson, Anjul Patney, Patrick M. Knupp, and John D. Owens SIAM Conference on Geometric and Physical Modeling (GD/SPM11), October 2011 DOI Slides |
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Efficient Maximal Poisson-Disk Sampling Mohamed S. Ebeida, Anjul Patney, Scott A. Mitchell, Andrew Davidson, Patrick M. Knupp, and John D. Owens ACM Transactions on Graphics (SIGGRAPH) ACM Preprint Slides Fast-Forward |
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Isotropic Conforming Refinement of Quadrilateral and Hexahedral Meshes using Two-Refinement Templates Mohamed S. Ebeida, Anjul Patney, John D. Owens, and Eric Mestreau International Journal for Numerical Methods in Engineering, 2011 DOI |
2010
2009
2008
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Real-Time Reyes: Programmable Pipelines and Research Challenges Course-talk at SIGGRAPH Asia 2008, Singapore Slides |
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Real-Time Reyes-Style Adaptive Surface Subdivision Anjul Patney and John D. Owens ACM Transactions on Graphics (SIGGRAPH Asia): ACM Preprint Slides Video Talk at UC Berkeley Graphics Lunch: Slides Talk at Microsoft Research: Slides |
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Texture Filter Memory - A Power-efficient and Scalable Texture Memory Architecture for Mobile Graphics Processors B. V. N. Silpa, Anjul Patney, Tushar Krishna, Preeti Ranjan Panda, and G. S. Visweswaran IEEE/ACM International Conference on Computer-Aided Design (ICCAD), November 2008 IEEE Xplore ACM |
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Efficient computation of sum-products on GPUs through software-managed cache Mark Silberstein, Assaf Schuster, Dan Geiger, Anjul Patney, and John D. Owens ACM International Conference on Supercomputing, June 2008 ACM Preprint |
"Somewhere, something incredible is waiting to be known." - Carl Sagan