2023
NIPS
NeurIPS 2023
OpenIllumination: A Multi-Illumination Dataset for Inverse Rendering Evaluation on Real Objects
Abstract
We introduce OpenIllumination, a real-world dataset containing over 108K images of 64 objects with diverse materials, captured under 72 camera views and a large number of different illuminations. For each image in the dataset, we provide accurate camera parameters, illumination ground truth, and foreground segmentation masks. Our dataset enables the quantitative evaluation of most inverse rendering and material decomposition methods for real objects. We examine several state-of-the-art inverse rendering methods on our dataset and compare their performances. The dataset and code can be found on the project page: https://oppo-us-research.github.io/OpenIllumination.
🌉
Interdisciplinary Bridge
— Computer Science and Computer Vision
🐝
Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy
Authors
Isabella Liu
,
Linghao Chen
,
Ziyang Fu
,
Liwen Wu
,
Haian Jin
,
Zhong Li
,
Chin Ming Ryan Wong
,
Yi Xu
,
Ravi Ramamoorthi
,
Zexiang Xu
,
Hao Su