Joonyoung Song

TL;DR: This paper reviews the second AIM learned ISP challenge and provides the description of the proposed solutions and results, defining the state-of-the-art for practical image signal processing pipeline modeling.

TL;DR: The second AIM learned ISP challenge as mentioned in this paper focused on real-world RAW-to-RGB mapping problem, where the goal was to map the original low-quality RAW images captured by the Huawei P20 device to the same photos obtained with the Canon 5D DSLR camera.

TL;DR: A novel unsupervised multispectral denoising method for satellite imagery using a wavelet directional cycle-consistent adversarial network (WavCycleGAN) and in contrast to the standard image-domain cycleGAN, this method introduces aWavelet directional learning scheme for effective denoised without sacrificing high-frequency components such as edges and detailed information.

TL;DR: Dementia severity can be objectively and accurately classified using a 3D-deep learning framework with rs-fMRI independent components and is an acceptable objective severity indicator in the absence of trained neuropsychologists.

TL;DR: PyNET-CA as discussed by the authors is an end-to-end mobile ISP deep learning algorithm for RAW to RGB reconstruction, which enhances PyNET, a recently proposed state-of-the-art model for mobile ISP, and improves its performance with channel attention and subpixel reconstruction module.