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

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...

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