Nima

Nima Kalantari

Assistant Professor

Computer Science and Engineering Department
Texas A&M University

Office: 527B, HRBB
Phone: (979) 862-4251
: nimak (at) tamu.edu

I am an Assistant Professor in the Computer Science and Engineering department at Texas A&M University. Previously, I was a postdoc in the CSE department at UC San Diego, where I worked with Ravi Ramamoorthi. I finished my Ph.D. in the ECE department at UC Santa Barbara under the supervision of Pradeep Sen.

I am looking to hire motivated graduate students who are interested in computer graphics and vision. If you are interested in working with me, please send me an email with your CV attached.

Research Interests

My primary research interests are in computer graphics with an emphasis on computational photography and rendering. Specifically, in recent years, I have focused on developing machine learning techniques for image synthesis in these two fields. Overall, my goal is to develop practical systems in a variety of computational photography and rendering applications with the goal of representing the world around us accurately.


Teaching

CSCE 689 - Deep Learning for Computer Graphics: Fall 2018


Selected Publications

For a complete list of my publications, please visit my Google Scholar profile.

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    Deep Adaptive Sampling for Low Sample Count Rendering

    Alexandr Kuznetsov, Nima Khademi Kalantari, and Ravi Ramamoorthi

    EGSR 2018
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    Deep Hybrid Real and Synthetic Training for Intrinsic Decomposition

    Sai Bi, Nima Khademi Kalantari, and Ravi Ramamoorthi

    EGSR 2018
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    Deep High Dynamic Range Imaging of Dynamic Scenes

    Nima Khademi Kalantari, and Ravi Ramamoorthi

    SIGGRAPH 2017
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    Patch-Based Optimization for Image-Based Texture Mapping

    Sai Bi, Nima Khademi Kalantari, and Ravi Ramamoorthi

    SIGGRAPH 2017
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    Light Field Video Capture Using a Learning-Based Hybrid Imaging System

    Ting-Chun Wang, Jun-Yan Zhu, Nima Khademi Kalantari, Alexei A. Efros, and Ravi Ramamoorthi

    SIGGRAPH 2017
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    Learning-Based View Synthesis for Light Field Cameras

    Nima Khademi Kalantari, Ting-Chun Wang, and Ravi Ramamoorthi

    SIGGRAPH Asia 2016
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    A Machine Learning Approach for Filtering Monte Carlo Noise

    Nima Khademi Kalantari, Steve Bako, and Pradeep Sen

    SIGGRAPH 2015
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    Robust Radiometric Calibration for Dynamic Scenes in the Wild

    Abhishek Badki, Nima Khademi Kalantari, and Pradeep Sen

    ICCP 2015
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    Improving Patch-Based Synthesis by Learning Patch Masks

    Nima Khademi Kalantari, Eli Shechtman, Soheil Darabi, Dan Goldman, and Pradeep Sen

    ICCP 2014
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    Patch-Based High Dynamic Range Video

    Nima Khademi Kalantari, Eli Shechtman, Connelly Barnes, Soheil Darabi, Dan B Goldman, and Pradeep Sen

    SIGGRAPH Asia 2013
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    Removing the Noise in Monte Carlo Rendering with General Image Denoising Algorithms

    Nima Khademi Kalantari, and Pradeep Sen

    Eurographics 2013
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    Robust Patch-Based HDR Reconstruction of Dynamic Scenes

    Pradeep Sen, Nima Khademi Kalantari, Maziar Yaesoubi, Soheil Darabi, Dan B Goldman, and Eli Shechtman

    SIGGRAPH Asia 2012
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    Fast Generation of Approximate Blue Noise Point Sets

    Nima Khademi Kalantari, and Pradeep Sen

    EGSR 2012
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    Efficient Computation of Blue Noise Point Sets through Importance Sampling

    Nima Khademi Kalantari, and Pradeep Sen

    EGSR 2011