This paper reviews the first AIM challenge on mapping camera RAW to RGB images with the
focus on proposed solutions and results. The participating teams were solving a real-world …

Medical image segmentation is one of the important steps in medical image analysis and
has a wide range of applications and research values in medical research and practice …

As the revolutionary improvement being made on the performance of smartphones over the
last decade, mobile photography becomes one of the most common practices among the …

Reconstructing RGB image from RAW data obtained with a mobile device is related to a
number of image signal processing (ISP) tasks, such as demosaicing, denoising, etc. Deep …

Conventional size object detection has been extensively studied, whereas researches
concerning ultrasmall object detection are rare due to lack of dataset. Here, considering that …

Medical image segmentation provides a reliable basis for diagnosis analysis and disease
treatment by capturing the global and local features of the target region. To learn global …

Image signal processing (ISP) is crucial for camera imaging, and neural networks (NN)
solutions are extensively deployed for daytime scenes. The lack of sufficient nighttime image …

The rapid progress in intelligent vehicle technology has led to a significant reliance on
computer vision and deep neural networks (DNNs) to improve road safety and driving …

Several recent studies have attempted to fully replace the conventional camera image signal
processing (ISP) pipeline with convolutional neural networks (CNNs). However, the previous …

Illumination estimation is the essential step of computational color constancy, one of the core
parts of various image processing pipelines of modern digital cameras. Having an accurate …