Abstract We present" Cross-Camera Convolutional Color Constancy"(C5), a learning-based
method, trained on images from multiple cameras, that accurately estimates a scene's …

Non-uniform and multi-illuminant color constancy are important tasks, the solution of which
will allow to discard information about lighting conditions in the image. Non-uniform …

Cameras currently allow access to two image states:(i) a minimally processed linear raw-
RGB image state (ie, raw sensor data); or (ii) a highly-processed nonlinear image state (eg …

Vision-based intelligent systems such as driver assistance systems and transportation
systems should take into account weather conditions. The presence of haze in images can …

In the human and computer vision, color constancy is the ability to perceive the true color of
objects in spite of changing illumination conditions. Color constancy is remarkably …

To achieve computer vision color constancy (CVCC), it is vital but challenging to estimate
scene illumination from a digital image, which distorts the true color of an object. Estimating …

Color constancy is the ability of the human visual system to perceive colors unchanged
independently of illumination. Giving a machine this feature will be beneficial in many fields …

The intrinsic properties of the ambient illuminant significantly alter the true colors of objects
within an image. Most existing color constancy algorithms assume a uniformly lit scene …

In this work, we propose a convolutional neural network based approach to estimate the
spectral reflectance of a surface and spectral power distribution of light from a single RGB …

Detecting fine-grained changes among a set of images taken at different times is a
challenging problem, which is important for the applications such as high-value scene …