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Mitsuba 2: A retargetable forward and inverse renderer
Modern rendering systems are confronted with a dauntingly large and growing set of
requirements: in their pursuit of realism, physically based techniques must increasingly …
requirements: in their pursuit of realism, physically based techniques must increasingly …
Differentiable monte carlo ray tracing through edge sampling
Gradient-based methods are becoming increasingly important for computer graphics,
machine learning, and computer vision. The ability to compute gradients is crucial to …
machine learning, and computer vision. The ability to compute gradients is crucial to …
Spatiotemporal reservoir resampling for real-time ray tracing with dynamic direct lighting
Efficiently rendering direct lighting from millions of dynamic light sources using Monte Carlo
integration remains a challenging problem, even for off-line rendering systems. We …
integration remains a challenging problem, even for off-line rendering systems. We …
[كتاب][B] Path-space differentiable rendering
C Zhang - 2022 - search.proquest.com
Abstract Physics-based differentiable rendering---which is concerned with estimating
derivatives of photorealistic rendering with respect to arbitrary scene parameters---has a …
derivatives of photorealistic rendering with respect to arbitrary scene parameters---has a …
Unbiased warped-area sampling for differentiable rendering
Differentiable rendering computes derivatives of the light transport equation with respect to
arbitrary 3D scene parameters, and enables various applications in inverse rendering and …
arbitrary 3D scene parameters, and enables various applications in inverse rendering and …
A differential theory of radiative transfer
Physics-based differentiable rendering is the task of estimating the derivatives of radiometric
measures with respect to scene parameters. The ability to compute these derivatives is …
measures with respect to scene parameters. The ability to compute these derivatives is …
Differentiable rendering of neural sdfs through reparameterization
We present a method to automatically compute correct gradients with respect to geometric
scene parameters in neural SDF renderers. Recent physically-based differentiable …
scene parameters in neural SDF renderers. Recent physically-based differentiable …
A new hybrid seagull optimization algorithm for feature selection
Hybrid algorithms have attracted more and more attention in the field of optimization
algorithms. In this paper, three hybrid algorithms are proposed to solve feature selection …
algorithms. In this paper, three hybrid algorithms are proposed to solve feature selection …
Learning to importance sample in primary sample space
Importance sampling is one of the most widely used variance reduction strategies in Monte
Carlo rendering. We propose a novel importance sampling technique that uses a neural …
Carlo rendering. We propose a novel importance sampling technique that uses a neural …
Risp: Rendering-invariant state predictor with differentiable simulation and rendering for cross-domain parameter estimation
This work considers identifying parameters characterizing a physical system's dynamic
motion directly from a video whose rendering configurations are inaccessible. Existing …
motion directly from a video whose rendering configurations are inaccessible. Existing …