Efficient and Accurate Physically-Based Differentiable Rendering

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Physically based rendering methods can create photorealistic images by simulating the propagation and interaction of light in a virtual scene. Given a scene description including the shape of objects, participating media, material properties, etc., the sim ...

Dr.Jit is a new just-in-time compiler for physically based rendering and its derivative. Dr.Jit expedites research on these topics in two ways: first, it traces high-level simulation code (e.g., written in Python) and aggressively simplifies and specialize ...

Physically-based differentiable rendering has recently emerged as an attractive new technique for solving inverse problems that recover complete 3D scene representations from images. The inversion of shape parameters is of particular interest but also pose ...

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Physically based rendering is a process for photorealistic digital image synthesis and one of the core problems in computer graphics. It involves simulating the light transport, i.e. the emission, propagation, and scattering of light through a virtual scen ...

Efficient and Accurate Physically-Based Differentiable Rendering

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Aggregating Spatial and Photometric Context for Photometric Stereo

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

A Full-Wave Reference Simulator for Computing Surface Reflectance

DyNCA: Real-time Dynamic Texture Synthesis Using Neural Cellular Automata

Deep Learning for 3D Surface Modelling and Reconstruction

Automatic Parameterization for Aerodynamic Shape Optimization via Deep Geometric Learning

Fast Adversarial Training With Adaptive Step Size

3DHumanGAN: 3D-Aware Human Image Generation with 3D Pose Mapping

Differentiable Physically Based Rendering: Algorithms, Systems and Applications

Dr.Jit: A Just-In-Time Compiler for Differentiable Rendering

Differentiable Signed Distance Function Rendering

Sub-micrometer morphology of human atherosclerotic plaque revealed by synchrotron radiation-based mu CT-A comparison with histology

GeoNeRF: Generalizing NeRF with Geometry Priors

Unsupervised Visual Entity Abstraction towards 2D and 3D Compositional Models

Meshing of Spiny Neuronal Morphologies using Union Operators

Gazebo Fluids: SPH-based simulation of fluid interaction with articulated rigid body dynamics

Masked Training of Neural Networks with Partial Gradients

Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery

On combining denoising with learning-based image decoding

Light Path Gradients for Forward and Inverse Rendering