activity
20242026
collaborators

9 papers

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.IV2026

Multi-Objective Pareto-Front Optimization for Efficient Adaptive VVC Streaming

Angeliki Katsenou, Vignesh V. Menon, Guoda Laurinaviciute +2

Adaptive video streaming has facilitated improved video streaming over the past years. A balance among coding performance objectives such as bitrate, video quality, and decoding co…

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

Content Adaptive Encoding For Interactive Game Streaming

Shakarim Soltanayev, Odysseas Zisimopoulos, Mohammad Ashraful Anam +3

Video-on-demand streaming has benefitted from \textit{content-adaptive encoding} (CAE), i.e., adaptation of resolution and/or quantization parameters for each scene based on convex…

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…