LIGHTS Dataset

Specular highlights are commonplace in images, however, methods for detecting them and in turn removing the phenomenon are particularly challenging. A reason for this, is due to the difficulty of creating a dataset for training or evaluation, as in the real-world we lack the necessary control over the environment. Therefore, we propose a novel physically-based rendered LIGHT Specularity (LIGHTS) Dataset for the evaluation of the specular highlight detection task. Our dataset consists of 18 high quality architectural scenes, where each scene is rendered with multiple views. In total we have 2,603 views with an average of 145 views per scene.

Light Specularity dataset

How to get the dataset

The dataset is available from Kaggle: https://www.kaggle.com/stuartjames/lights

How to cite the dataset (Bib)

The dataset was provided as part of the following paper. Please cite this paper to acknowledge the efforts of the authors in creating it.

@misc{Elkhouly:arXiv21,
  author = {Elkhouly, M. D. and Tsesmelis, T. and {Del Bue}, A.},
  title = {LIGHTS: LIGHT Specularity Dataset for specular detection in Multi-view},
  archivePrefix = {arXiv},
  year = {2021},


}