Emotion recognition is the ability to precisely infer human emotions from numerous sources
and modalities using questionnaires, physical signals, and physiological signals. Recently …

In this tutorial paper, we look into the evolution and prospect of network architecture and
propose a novel conceptual architecture for the 6th generation (6G) networks. The proposed …

We present DiffBIR, a general restoration pipeline that could handle different blind image
restoration tasks in a unified framework. DiffBIR decouples blind image restoration problem …

Text-to-image personalization aims to teach a pre-trained diffusion model to reason about
novel, user provided concepts, embedding them into new scenes guided by natural …

Recognition in low quality face datasets is challenging because facial attributes are
obscured and degraded. Advances in margin-based loss functions have resulted in …

Federated learning (FL) has emerged as a powerful machine learning technique that
enables the development of models from decentralized data sources. However, the …

Blind face restoration is a highly ill-posed problem that often requires auxiliary guidance to
1) improve the map** from degraded inputs to desired outputs, or 2) complement high …

The performance of face recognition system degrades when the variability of the acquired
faces increases. Prior work alleviates this issue by either monitoring the face quality in pre …

Machine learning (ML) models have been widely applied to various applications, including
image classification, text generation, audio recognition, and graph data analysis. However …

Generating synthetic datasets for training face recognition models is challenging because
dataset generation entails more than creating high fidelity images. It involves generating …