Search Results for author: Paul Debevec

Found 11 papers, 3 papers with code

Jointly Optimizing Color Rendition and In-Camera Backgrounds in an RGB Virtual Production Stage

no code implementations24 May 2022 Chloe LeGendre, Lukas Lepicovsky, Paul Debevec

While the LED panels used in virtual production systems can display vibrant imagery with a wide color gamut, they produce problematic color shifts when used as lighting due to their peaky spectral output from narrow-band red, green, and blue LEDs.

A New Dimension in Testimony: Relighting Video with Reflectance Field Exemplars

no code implementations6 Apr 2021 Loc Huynh, Bipin Kishore, Paul Debevec

We estimate the lighting environment of the input video footage and use the subject's reflectance field to create synthetic images of the subject illuminated by the input lighting environment.

Lighting Estimation

Baking Neural Radiance Fields for Real-Time View Synthesis

1 code implementation ICCV 2021 Peter Hedman, Pratul P. Srinivasan, Ben Mildenhall, Jonathan T. Barron, Paul Debevec

Neural volumetric representations such as Neural Radiance Fields (NeRF) have emerged as a compelling technique for learning to represent 3D scenes from images with the goal of rendering photorealistic images of the scene from unobserved viewpoints.

Neural Light Transport for Relighting and View Synthesis

1 code implementation9 Aug 2020 Xiuming Zhang, Sean Fanello, Yun-Ta Tsai, Tiancheng Sun, Tianfan Xue, Rohit Pandey, Sergio Orts-Escolano, Philip Davidson, Christoph Rhemann, Paul Debevec, Jonathan T. Barron, Ravi Ramamoorthi, William T. Freeman

In particular, we show how to fuse previously seen observations of illuminants and views to synthesize a new image of the same scene under a desired lighting condition from a chosen viewpoint.

Learning Illumination from Diverse Portraits

no code implementations5 Aug 2020 Chloe LeGendre, Wan-Chun Ma, Rohit Pandey, Sean Fanello, Christoph Rhemann, Jason Dourgarian, Jay Busch, Paul Debevec

We present a learning-based technique for estimating high dynamic range (HDR), omnidirectional illumination from a single low dynamic range (LDR) portrait image captured under arbitrary indoor or outdoor lighting conditions.

Lighting Estimation

DeepLight: Learning Illumination for Unconstrained Mobile Mixed Reality

no code implementations CVPR 2019 Chloe LeGendre, Wan-Chun Ma, Graham Fyffe, John Flynn, Laurent Charbonnel, Jay Busch, Paul Debevec

We present a learning-based method to infer plausible high dynamic range (HDR), omnidirectional illumination given an unconstrained, low dynamic range (LDR) image from a mobile phone camera with a limited field of view (FOV).

Mixed Reality

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