Rescaling Network

Rescaling networks aim to efficiently and accurately resize images, addressing the inherent information loss in traditional downscaling methods. Current research focuses on developing invertible network architectures, such as those based on residual blocks and decoupled flows, to enable lossless or near-lossless bidirectional transformations between high and low-resolution images, often incorporating techniques to handle arbitrary scaling factors. These advancements improve image quality in applications like super-resolution, video compression, and image editing, offering significant improvements over conventional methods in terms of both visual fidelity and computational efficiency.