Publication

Inverse Path Tracing for Joint Material and Lighting Estimation

Computer Vision and Pattern Recognition (CVPR)


Abstract

Modern computer vision algorithms have brought significant advancement to 3D geometry reconstruction. However, illumination and material reconstruction remain less studied, with current approaches assuming very simplified models for materials and illumination. We introduce Inverse Path Tracing, a novel approach to jointly estimate the material properties of objects and light sources in indoor scenes by using an invertible light transport simulation. We assume a coarse geometry scan, along with corresponding images and camera poses. The key contribution of this work is an accurate and simultaneous retrieval of light sources and physically based material properties (e.g., diffuse reflectance, specular reflectance, roughness, etc.) for the purpose of editing and re-rendering the scene under new conditions. To this end, we introduce a novel optimization method using a differentiable Monte Carlo renderer that computes derivatives with respect to the estimated unknown illumination and material properties. This enables joint optimization for physically correct light transport and material models using a tailored stochastic gradient descent.

Related Publications

All Publications

NeurIPS - December 1, 2020

Continuous Surface Embeddings

Natalia Neverova, David Novotny, Vasil Khalidov, Marc Szafraniec, Patrick Labatut, Andrea Vedaldi

NeurIPS - December 4, 2020

Demystifying Contrastive Self-Supervised Learning: Invariances, Augmentations and Dataset Biases

Senthil Purushwalkam, Abhinav Gupta

ICSE - November 23, 2020

Predictive Test Selection

Mateusz Machalica, Alex Samylkin, Meredith Porth, Satish Chandra

3DV - November 25, 2020

MonoClothCap: Towards Temporally Coherent Clothing Capture from Monocular RGB Video

Donglai Xiang, Fabian Prada, Chenglei Wu, Jessica Hodgins

To help personalize content, tailor and measure ads, and provide a safer experience, we use cookies. By clicking or navigating the site, you agree to allow our collection of information on and off Facebook through cookies. Learn more, including about available controls: Cookies Policy