Conventional illuminant estimation methods were developed for scenes with a uniform
illumination, while recently developed methods, such as pixel-wise methods, estimate the …

Deep Neural Networks (DNNs) have been widely used for illumination estimation, which is
time-consuming and requires sensor-specific data collection. Our proposed method uses a …

Great efforts have been made on illuminant estimation in both academia and industry,
leading to the development of various statistical- and learning-based methods. Little attention, …

Deep neural networks (DNNs) have been widely used for illuminant estimation, which
commonly requires great efforts to collect sensor-specific data. In this paper, we propose a dual-…

An image is commonly white balanced using a white point that is considered to accurately
characterize the scene illumination color (eg, the white point estimated by the main camera on …

Illuminant estimation is critically important in computational color constancy, which has
attracted great attentions and motivated the development of various statistical- and learning-…

MCNP full-reactor models of the SLOWPOKE-2 and ZED-2 research reactors have been
used for calculating gamma spectra and dose rates at locations where measurements were …

Monocular depth estimation has attracted extensive attention and made great progress in
recent years. However, the performance still lags far behind LiDAR-based depth completion …

In modern image signal processors (ISPs), many modules have adopted deep neural networks
(DNNs). This study explores whether a single DNN can effectively replace both the auto …

Based on the observation that whitish surfaces are perhaps a better indicator of the color of
the illuminant than strongly colored surfaces, we propose a new illumination estimation …