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Found 6 papers, 1 papers with code
Random-Access Neural Compression of Material Textures
The continuous advancement of photorealism in rendering is accompanied by a growth in texture data and, consequently, increasing storage and memory demands.
Stochastic Texture Filtering
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.
Fast and High-Quality Image Denoising via Malleable Convolutions
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.
Procedural Kernel Networks
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.
Image Stylization: From Predefined to Personalized
We present a framework for interactive design of new image stylizations using a wide range of predefined filter blocks.
Handheld Multi-Frame Super-Resolution
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.
