3 accepted papers
No-Reference Video Quality Assessment (NR-VQA) plays an essential role in improving the viewing experience of end-users. Driven by deep learning, recent NR-VQA models based on Convolutional Neural Networks (CNNs) and Transformers have achieved outstanding performance. To build a reliable and practic…
Automatically evaluating the quality of in-the-wild videos is challenging since both the distortion types and reference videos are unknown. In general, humans can make a fast and accurate judgment for video quality. Fortunately, deep neural networks have been developed to effectively model the human…
In recent years, Face Image Quality Assessment (FIQA) has become an indispensable part of the face recognition system to guarantee the stability and reliability of recognition performance in an unconstrained scenario. For this purpose, the FIQA method should consider both the intrinsic property and…