by America Ortiz | Nov 29, 2023 | Capture, Visual Computing
An Implicit Physical Face Model Driven by Expression and Style We propose a new face model based on a data-driven implicit neural physics model that can be driven by both expression and style separately. At the core, we present a framework for learning implicit...
by America Ortiz | Oct 9, 2023 | Capture, Visual Computing
A Perceptual Shape Loss for Monocular 3D Face Reconstruction In this work, we propose a new loss function for monocular face capture, inspired by how humans would perceive the quality of a 3D face reconstruction given a particular image. It is widely known that...
by America Ortiz | Oct 2, 2023 | Capture, Visual Computing
ReNeRF: Relightable Neural Radiance Fields with Nearfield Lighting In this paper, we target the application scenario of capturing high-fidelity assets for neural relighting in controlled studio conditions, but without requiring a dense light stage. Instead, we...
by America Ortiz | Aug 31, 2023 | Machine Learning
The Score-Difference Flow for Implicit Generative Modeling We present the score difference (SD) between arbitrary target and source distributions as a flow that optimally reduces the Kullback-Leibler divergence between them. July 2023 Transactions on Machine Learning...
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...
