A Benchmark for Burst Color Constancy

Abstract

Burst Color Constancy (CC) is a recently proposed approach that challenges the conventional single-frame color constancy. The conventional approach is to use a single frame - shot frame - to estimate the scene illumination color. In burst CC, multiple frames from the view finder sequence are used to estimate the color of the shot frame. However, there are no realistic large-scale color constancy datasets with sequence input for method evaluation. In this work, a new such CC benchmark is introduced. The benchmark comprises of (1) 600 real-world sequences recorded with a high-resolution mobile phone camera, (2) a fixed train-test split which ensures consistent evaluation, and (3) a baseline method which achieves high accuracy in the new benchmark and the dataset used in previous works. Results for more than 20 well-known color constancy methods including the recent state-of-the-arts are reported in our experiments.

Cite

Text

Qian et al. "A Benchmark for Burst Color Constancy." European Conference on Computer Vision Workshops, 2020. doi:10.1007/978-3-030-67070-2_22

Markdown

[Qian et al. "A Benchmark for Burst Color Constancy." European Conference on Computer Vision Workshops, 2020.](https://mlanthology.org/eccvw/2020/qian2020eccvw-benchmark/) doi:10.1007/978-3-030-67070-2_22

BibTeX

@inproceedings{qian2020eccvw-benchmark,
  title     = {{A Benchmark for Burst Color Constancy}},
  author    = {Qian, Yanlin and Käpylä, Jani and Kämäräinen, Joni-Kristian and Koskinen, Samu and Matas, Jiri},
  booktitle = {European Conference on Computer Vision Workshops},
  year      = {2020},
  pages     = {359-375},
  doi       = {10.1007/978-3-030-67070-2_22},
  url       = {https://mlanthology.org/eccvw/2020/qian2020eccvw-benchmark/}
}