Face super-resolution aims to reconstruct a high-resolution face image from a low-resolution
face image. Previous methods typically employ an encoder-decoder structure to extract …

Abstract Knowledge tracing (KT) is the task of predicting students' future performance based
on their historical learning interaction data. With the rapid advancement of attention …

Face Super-Resolution (FSR) is critical for bolstering intelligent security in Internet of Things
(IoT) systems. Recent deep learning-driven FSR algorithms have attained remarkable …

The object of image super-resolution reconstruction is to overcome the limitations imposed
by hardware imaging conditions and patterns, aiming to restore high-frequency details in …

The goal of Blind Face Restoration is to recover high-quality images from low-quality images
suffering from unknown degradations, posing a significantly challenging problem. In recent …

Face restoration (FR) is a specialized field within image restoration that aims to recover low-
quality (LQ) face images into high-quality (HQ) face images. Recent advances in deep …

Recently, CNN and Transformer hybrid networks demonstrated excellent performance in
face super-resolution (FSR) tasks. Since numerous features at different scales in hybrid …

Recently, the contrastive learning paradigm has achieved remarkable success in high-level
tasks such as classification, detection, and segmentation. However, contrastive learning …