A Real-world Display Inverse Rendering Dataset
Seokjun Choi, Hoon-Gyu Chung, Yujin Jeon, Giljoo Nam, Seung-Hwan Baek

TL;DR
This paper introduces the first real-world display-camera dataset for inverse rendering, enabling better development and evaluation of display-based inverse rendering methods with diverse objects and ground-truth geometry.
Contribution
It provides a novel, calibrated display-camera dataset capturing diverse objects with ground-truth geometry, facilitating research in display-based inverse rendering.
Findings
Existing methods are evaluated on the dataset.
A simple baseline outperforms state-of-the-art inverse rendering methods.
The dataset enables synthesis under arbitrary display patterns.
Abstract
Inverse rendering aims to reconstruct geometry and reflectance from captured images. Display-camera imaging systems offer unique advantages for this task: each pixel can easily function as a programmable point light source, and the polarized light emitted by LCD displays facilitates diffuse-specular separation. Despite these benefits, there is currently no public real-world dataset captured using display-camera systems, unlike other setups such as light stages. This absence hinders the development and evaluation of display-based inverse rendering methods. In this paper, we introduce the first real-world dataset for display-based inverse rendering. To achieve this, we construct and calibrate an imaging system comprising an LCD display and stereo polarization cameras. We then capture a diverse set of objects with diverse geometry and reflectance under one-light-at-a-time (OLAT) display…
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Taxonomy
TopicsComputer Graphics and Visualization Techniques · 3D Shape Modeling and Analysis · Advanced Vision and Imaging
