This paper proposes the optimized quality feature learning via a multi-channel convolutional neural network (CNN) with the gated recurrent unit (GRU) for no- ...

Motivated by the self-supervised learning (SSL), this paper proposes a multi-channel CNN model using non-human annotated supervision signals for image-level ...

In this work, we propose a no-reference video quality assessment method, aiming to achieve high-generalization capability in cross-content, -resolution and - ...

Jun 4, 2023 · Optimized Quality Feature Learning for Video Quality Assessment. Ngai-Wing Kwong 1. ,. Yui-Lam Chan 1. ,. Sik-Ho Tsang 2.

Sep 14, 2024 · SR4KVQA is one of the very first quality assessment databases with in-lab mean opinion score labels for SR-generated 4K videos.

Dec 24, 2023 · Our focus in this work is on designing semi-supervised NR VQA method with limited labelled along with unlabelled data. Since UGC videos have ...

In this work we propose a novel method to evaluate the quality of enhanced videos. Perceived quality of a video depends on both technical aspects, ...

Dec 10, 2022 · In this paper, we propose a novel NR-VQA algorithm that integrates the fusion of temporal statistics of local and global image features with an ensemble ...

Apr 24, 2024 · This challenge deals with the design of deep learning-based methods for blind video quality metrics, targeting user-generated content.

The goal was targeted to optimize the Quality of Experience (QoE) of real-time video using dynamic predictions by means of Deep Reinforcement Learning (DRL) ...