  Temporal 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
temporal CC, multiple frames from the view finder sequence are used to estimate
the color. However, there are no realistic large scale temporal color constancy
datasets for method evaluation. In this work, a new temporal 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.
