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eess.IV2026

FGSVQA: Frequency-Guided Short-form Video Quality Assessment

Xinyi Wang, Angeliki Katsenou, Junxiao Shen +1

Short-form video poses new challenges to the quality assessment of user-generated content (UGC) due to its complex generation pipeline, rapid content variation, and mixed distortio…

eess.IV2025

Guiding WaveMamba with Frequency Maps for Image Debanding

Xinyi Wang, Smaranda Tasmoc, Nantheera Anantrasirichai +1

Compression at low bitrates in modern codecs often introduces banding artifacts, especially in smooth regions such as skies. These artifacts degrade visual quality and are common i…

eess.IV2025

CAMP-VQA: Caption-Embedded Multimodal Perception for No-Reference Quality Assessment of Compressed Video

Xinyi Wang, Angeliki Katsenou, Junxiao Shen +1

The prevalence of user-generated content (UGC) on platforms such as YouTube and TikTok has rendered no-reference (NR) perceptual video quality assessment (VQA) vital for optimizing…

eess.IV2025

DIVA-VQA: Detecting Inter-frame Variations in UGC Video Quality

Xinyi Wang, Angeliki Katsenou, David Bull

The rapid growth of user-generated (video) content (UGC) has driven increased demand for research on no-reference (NR) perceptual video quality assessment (VQA). NR-VQA is a key co…

eess.IV2025

ReLaX-VQA: Residual Fragment and Layer Stack Extraction for Enhancing Video Quality Assessment

Xinyi Wang, Angeliki Katsenou, David Bull

With the rapid growth of User-Generated Content (UGC) exchanged between users and sharing platforms, the need for video quality assessment in the wild is increasingly evident. UGC…

eess.IV2024

Rate-Quality or Energy-Quality Pareto Fronts for Adaptive Video Streaming?

Angeliki Katsenou, Xinyi Wang, Daniel Schien +1

Adaptive video streaming is a key enabler for optimising the delivery of offline encoded video content. The research focus to date has been on optimisation, based solely on rate-qu…