14 citations · 14 across the 5 of their papers we have counts for
6 papers
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…
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…
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…
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…
Comparative Study of Hardware and Software Power Measurements in Video Compression
Angeliki Katsenou, Xinyi Wang, Daniel Schien +1
The environmental impact of video streaming services has been discussed as part of the strategies towards sustainable information and communication technologies. A first step towar…
BVI-CC: A Dataset for Research on Video Compression and Quality Assessment
Angeliki V. Katsenou, Fan Zhang, Mariana Afonso +2
The video technology scenery has been very vivid over the past years, with novel video coding technologies introduced that promise improved compression performance over state-of-th…