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Kernel-Based Frame Interpolation for Spatio-Temporally Adaptive Rendering

Kernel-Based Frame Interpolation for Spatio-Temporally Adaptive Rendering

by Melanie Cadalbert | Jul 23, 2023 | Rendering, Video Processing, Visual Computing

Kernel-Based Frame Interpolation for Spatio-TemporallyAdaptive Rendering We propose a frame interpolation method for rendered content with two key features. First, a kernel based frame synthesis model which predicts the interpolated frame as a linear mapping of the...
Graph-Based Synthesis for Skin Micro Wrinkles

Graph-Based Synthesis for Skin Micro Wrinkles

by Martina Megaro | Jul 3, 2023 | Capture, Machine Learning, VFX

Graph-Based Synthesis for Skin Micro Wrinkles   We present a novel graph-based simulation approach for generating micro wrinkle geometry on human skin, which can easily scale up to the micro-meter range and millions of wrinkles. July 3, 2023 Eurographics Symposium on...
Deep Compositional Denoising on Frame Sequences

Deep Compositional Denoising on Frame Sequences

by Melanie Cadalbert | Jun 26, 2023 | Rendering, Video Processing, Visual Computing

Deep Compositional Denoising on Frame Sequences Path tracing is the prevalent rendering algorithm in the animated movies and visual effects industry, thanks to its simplicity and ability to render physically plausible lighting effects. However, we must simulate...
Continuous Landmark Detection with 3D Queries

Continuous Landmark Detection with 3D Queries

by Melanie Cadalbert | Jun 4, 2023 | Rendering, Video Processing, Visual Computing

Continuous Landmark Detection with 3D Queries We propose the first facial landmark detection network that can predict continuous, unlimited landmarks, allowing to specify the number and location of the desired landmarks at inference time. Our method combines a simple...
Video Compression with Entropy-Constrained Neural Representations

Video Compression with Entropy-Constrained Neural Representations

by Melanie Cadalbert | Jun 4, 2023 | Rendering, Video Processing, Visual Computing

Video Compression with Entropy-Constrained Neural Representations We propose a novel convolutional architecture for video representation that better represents spatio-temporal information and a training strategy capable of jointly optimizing rate and distortion. June...
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