no code implementations • 26 May 2023 • Karthik Vaidyanathan, Marco Salvi, Bartlomiej Wronski, Tomas Akenine-Möller, Pontus Ebelin, Aaron Lefohn
The continuous advancement of photorealism in rendering is accompanied by a growth in texture data and, consequently, increasing storage and memory demands.
no code implementations • 9 May 2023 • Marcos Fajardo, Bartlomiej Wronski, Marco Salvi, Matt Pharr
2D texture maps and 3D voxel arrays are widely used to add rich detail to the surfaces and volumes of rendered scenes, and filtered texture lookups are integral to producing high-quality imagery.
no code implementations • 2 Jan 2022 • Yifan Jiang, Bartlomiej Wronski, Ben Mildenhall, Jonathan T. Barron, Zhangyang Wang, Tianfan Xue
These spatially-varying kernels are produced by an efficient predictor network running on a downsampled input, making them much more efficient to compute than per-pixel kernels produced by a full-resolution image, and also enlarging the network's receptive field compared with static kernels.
no code implementations • 17 Dec 2021 • Bartlomiej Wronski
In this work, we introduce Procedural Kernel Networks (PKNs), a family of machine learning models which generate parameters of image filter kernels or other traditional algorithms.
no code implementations • 22 Feb 2020 • Ignacio Garcia-Dorado, Pascal Getreuer, Bartlomiej Wronski, Peyman Milanfar
We present a framework for interactive design of new image stylizations using a wide range of predefined filter blocks.
3 code implementations • 8 May 2019 • Bartlomiej Wronski, Ignacio Garcia-Dorado, Manfred Ernst, Damien Kelly, Michael Krainin, Chia-Kai Liang, Marc Levoy, Peyman Milanfar
In this paper, we supplant the use of traditional demosaicing in single-frame and burst photography pipelines with a multiframe super-resolution algorithm that creates a complete RGB image directly from a burst of CFA raw images.