Nima Khademi Kalantari
Most Recent Affiliation(s):
- University of California, Santa Barbara, Texas A&M University
Other / Past Affiliation(s):
- Texas A&M University
Location:
- College Station, Texas, United States of America
Learning Category: Presentation(s):
![PhotoMat: A Material Generator Learned from Single Flash Photos](https://history.siggraph.org/wp-content/uploads/2024/02/2023-Tech-Papers-Zhou_PhotoMat-A-Material-Generator-Learned-from-Single-Flash-Photos-150x150.jpg)
Type: [Technical Papers]
PhotoMat: A Material Generator Learned from Single Flash Photos Presenter(s): [Hasan] [Deschaintre] [Guerrero] [Hold-Geoffroy] [Sunkavalli] [Kalantari]
[SIGGRAPH 2023]
![Foveated Monte-Carlo Denoising](https://history.siggraph.org/wp-content/uploads/2022/08/2021-Poster-07-Milef_Foveated-Monte-Carlo-Denoising-01-150x150.jpg)
Type: [Posters]
Foveated Monte-Carlo Denoising Presenter(s): [Milef] [Kalantari]
Entry No.: [07]
[SIGGRAPH 2021]
![Single Image HDR Reconstruction Using a CNN with Masked Featuresand Perceptual Loss](https://history.siggraph.org/wp-content/uploads/2022/09/2020-Technical-Papers-Santos_Single-Image-HDR-Reconstruction-Using-a-CNN-with-Masked-Features-and-Perceptual-Loss-150x150.jpg)
Type: [Technical Papers]
Single Image HDR Reconstruction Using a CNN with Masked Featuresand Perceptual Loss Presenter(s): [Santos] [Ren] [Kalantari]
[SIGGRAPH 2020]
![Local light field fusion: practical view synthesis with prescriptive sampling guidelines](https://history.siggraph.org/wp-content/uploads/2023/01/2019-Technical-Papers-Mildenhall_Local-Light-Field-Fusion_-Practical-View-Synthesis-with-Prescriptive-Sampling-Guidelines-150x150.jpg)
Type: [Technical Papers]
Local light field fusion: practical view synthesis with prescriptive sampling guidelines Presenter(s): [Mildenhall] [Srinivasan] [Ortiz-Cayon] [Kalantari] [Ramamoorthi] [Ng] [Kar]
[SIGGRAPH 2019]
![Deep high dynamic range imaging of dynamic scenes](https://history.siggraph.org/wp-content/uploads/2023/02/2017-Technical-Papers-Kalantari_Deep-High-Dynamic-Range-Imaging-of-Dynamic-Scenes-150x150.jpg)
Type: [Technical Papers]
Deep high dynamic range imaging of dynamic scenes Presenter(s): [Kalantari] [Ramamoorthi]
[SIGGRAPH 2017]
![Light field video capture using a learning-based hybrid imaging system](https://history.siggraph.org/wp-content/uploads/2023/02/2017-Technical-Papers-Wang_Light-Field-Video-Capture-Using-a-Learning-Based-Hybrid-Imaging-System-150x150.jpg)
Type: [Technical Papers]
Light field video capture using a learning-based hybrid imaging system Presenter(s): [Wang] [Zhu] [Kalantari] [Efros] [Ramamoorthi]
[SIGGRAPH 2017]
![Patch-based optimization for image-based texture mapping](https://history.siggraph.org/wp-content/uploads/2023/02/2017-Technical-Papers-Bi_Patch-based-optimization-for-image-based-texture-mapping-150x150.jpg)
Type: [Technical Papers]
Patch-based optimization for image-based texture mapping Presenter(s): [Bi] [Kalantari] [Ramamoorthi]
[SIGGRAPH 2017]
![A machine learning approach for filtering Monte Carlo noise](https://history.siggraph.org/wp-content/uploads/2022/07/2015-SIGGRAPH-Image-Not-Available-150x150.jpg)
Type: [Technical Papers]
A machine learning approach for filtering Monte Carlo noise Presenter(s): [Kalantari] [Bako] [Sen]
[SIGGRAPH 2015]
Role(s):
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