The Laval Photometric Indoor HDR Dataset
Full-HDR photometric high resolution indoor panoramas
This dataset contains 2362 high resolution indoor panoramas, captured using a Canon 5D Mark III and a robotic panoramic tripod head. The camera, with its Sigma 8mm fisheye lens, was calibrated using 130 scenes with the corresponding photometric measurments from a Konica Minolta CL-200A chroma meter. Each capture was multi-exposed (22 f-stops) and is fully HDR, representing luminance values. Panoramas were stitched from 6 captures (60 degrees azimuth increment) and were captured in a wide variety of indoor environments.
This work extends the Laval Indoor HDR Dataset.
To obtain the dataset, you can:
- Request full access to the dataset if you are an academic researcher. First fill the End User Licence Agreement and return it to Jean-Francois Lalonde by email at jflalonde at gel dot ulaval dot ca. For other uses, see Usage below.
- Download a ZIP archive containing a preview dataset (100 samples, 2048x1024, full-HDR). Note that the usage of this preview dataset is restricted to academic or non-profit researchers (see Usage).
- Consult this preview where all the dataset is exposed in a single page. The data is however tonemapped (LDR), of limited resolution (512x256), and JPEG compressed, so it should only be used as an overview.
This data is available for general use by:
- Non-profit organisation (for academic or government-sponsored researchers): this license does not grant the rights to use the data set or any derivation of it for commercial activities neither for redistribution. This license is free.
- For-profit organisation: this license allows the access to the data, the use of the data to create or improve models and resulting output, with the right to make the output available to third parties or to use if for your benefit. The dataset itself cannot be made available to third party. For any commercial use please contact Jean-Francois Lalonde at jflalonde at gel dot ulaval dot ca.
If you use this data in a publication, we ask you to cite these papers:
- Bolduc, C., Giroux, J., Hébert, M., Demers, C., and Lalonde, J.F. Beyond the Pixel: a Photometrically Calibrated HDR Dataset for Luminance and Color Prediction
- Gardner, M.-A., Sunkavalli, K., Yumer, E., Shen, X., Gambaretto, E., Gagné, C., and Lalonde, J.F. Learning to Predict Indoor Illumination from a Single Image
This research was supported by Sentinel North, NSERC grant RGPIN 2020-04799, and the Digital Research Alliance Canada. The authors thank Mojtaba Parsaee and Anthony Gagnon for their help with the chroma meter and the Theta Z1 calibration.
For the original dataset, the authors gratefully acknowledge Adobe for funding this project. We also thank Jean-Michel Fortin, Samuel Delisle, Guillaume Doyon, and Gabriel Lavin-Muller for their help with data capture and processing. Thanks also to Dominic Bilodeau, Louis-Emile Robitaille and Frédéric St-Pierre who participated in earlier iterations of the data capture process.