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    Recent Advances in Adaptive Sampling and Reconstruction for Monte Carlo Rendering
    (The Eurographics Association and John Wiley & Sons Ltd., 2015) Zwicker, Matthias; Jarosz, Wojciech; Lehtinen, Jaakko; Moon, Bochang; Ramamoorthi, Ravi; Rousselle, Fabrice; Sen, Pradeep; Soler, Cyril; Yoon, Sungeui E.; K. Hormann and O. Staadt
    Monte Carlo integration is firmly established as the basis for most practical realistic image synthesis algorithms because of its flexibility and generality. However, the visual quality of rendered images often suffers from estimator variance, which appears as visually distracting noise. Adaptive sampling and reconstruction algorithms reduce variance by controlling the sampling density and aggregating samples in a reconstruction step, possibly over large image regions. In this paper we survey recent advances in this area. We distinguish between “a priori” methods that analyze the light transport equations and derive sampling rates and reconstruction filters from this analysis, and “a posteriori” methods that apply statistical techniques to sets of samples to drive the adaptive sampling and reconstruction process. They typically estimate the errors of several reconstruction filters, and select the best filter locally to minimize error. We discuss advantages and disadvantages of recent state-of-the-art techniques, and provide visual and quantitative comparisons. Some of these techniques are proving useful in real-world applications, and we aim to provide an overview for practitioners and researchers to assess these approaches. In addition, we discuss directions for potential further improvements.
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    Recent Advances in Facial Appearance Capture
    (The Eurographics Association and John Wiley & Sons Ltd., 2015) Klehm, Oliver; Rousselle, Fabrice; Papas, Marios; Bradley, Derek; Hery, Christophe; Bickel, Bernd; Jarosz, Wojciech; Beeler, Thabo; K. Hormann and O. Staadt
    Facial appearance capture is now firmly established within academic research and used extensively across various application domains, perhaps most prominently in the entertainment industry through the design of virtual characters in video games and films. While significant progress has occurred over the last two decades, no single survey currently exists that discusses the similarities, differences, and practical considerations of the available appearance capture techniques as applied to human faces. A central difficulty of facial appearance capture is the way light interacts with skin-which has a complex multi-layered structure-and the interactions that occur below the skin surface can, by definition, only be observed indirectly. In this report, we distinguish between two broad strategies for dealing with this complexity. “Image-based methods” try to exhaustively capture the exact face appearance under different lighting and viewing conditions, and then render the face through weighted image combinations. “Parametric methods” instead fit the captured reflectance data to some parametric appearance model used during rendering, allowing for a more lightweight and flexible representation but at the cost of potentially increased rendering complexity or inexact reproduction. The goal of this report is to provide an overview that can guide practitioners and researchers in assessing the tradeoffs between current approaches and identifying directions for future advances in facial appearance capture.