Adaptive Frequency

Adaptive frequency processing in computer vision and machine learning focuses on enhancing the representation and manipulation of image and signal information across different frequency bands. Current research emphasizes developing novel network architectures, such as adaptive frequency enhancement networks and frequency-adapting groups, that dynamically adjust processing based on the specific frequency content, improving performance in tasks like image deraining, camouflaged object detection, and video editing. This approach leads to more efficient and robust models by selectively enhancing or suppressing specific frequencies, ultimately improving accuracy and reducing computational costs in various applications.