MAE-VQA: an efficient and accurate end-to-end video quality assessment method for user generated content videos

• Main Author: Wang, Chuhan
• Other Authors: Lin Weisi
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2024
• Subjects: Computer and Information Science
• Online Access: https://hdl.handle.net/10356/178566
• Institution: Nanyang Technological University

In the digital age, the proliferation of user-generated content (UGC) videos presents unique challenges in maintaining video quality across diverse platforms. In this project, we propose Masked Auto-Encoder model for no-reference video quality assessment (NR-VQA) problem. To our best knowledge, we a...