29 citations · 83 across the 24 of their papers we have counts for
25 papers
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…
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…
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…
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…
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…
Connectivity for AI enabled cities -- A field survey based study of emerging economies
Dibakar Das, Jyotsna Bapat, Angeliki Katsenou +1
The impact of Artificial Intelligence (AI) is transforming various aspects of urban life, including, governance, policy and planning, healthcare, sustainability, economics, entrepr…
Connecting the Unconnected: A DT Case Study of Nomadic Nodes Deployment in Nepal
Ioannis Mavromatis, Angeliki Katsenou, Klodian Bardhi +2
This paper addresses the challenge of robust cellular connectivity in dense, underdeveloped urban environments, specifically focusing on Kathmandu, Nepal. As cities grow, existing…
Decoding Complexity-Rate-Quality Pareto-Front for Adaptive VVC Streaming
Angeliki Katsenou, Vignesh V Menon, Adam Wieckowski +2
Pareto-front optimization is crucial for addressing the multi-objective challenges in video streaming, enabling the identification of optimal trade-offs between conflicting goals s…
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…
UGC Quality Assessment: Exploring the Impact of Saliency in Deep Feature-Based Quality Assessment
Xinyi Wang, Angeliki Katsenou, David Bull
The volume of User Generated Content (UGC) has increased in recent years. The challenge with this type of content is assessing its quality. So far, the state-of-the-art metrics are…
Subjective assessment of the impact of a content adaptive optimiser for compressing 4K HDR content with AV1
Vibhoothi, Angeliki Katsenou, François Pitié +2
Since 2015 video dimensionality has expanded to higher spatial and temporal resolutions and a wider colour gamut. This High Dynamic Range (HDR) content has gained traction in the c…
Recommendations for Verifying HDR Subjective Testing Workflows
Vibhoothi, Angeliki Katsenou, John Squires +2
Over the past few years, there has been an increase in the demand and availability of High Dynamic Range (HDR) displays and content. To ensure the production of high-quality materi…
Comparison of HDR quality metrics in Per-Clip Lagrangian multiplier optimisation with AV1
Vibhoothi, François Pitié, Angeliki Katsenou +3
The complexity of modern codecs along with the increased need of delivering high-quality videos at low bitrates has reinforced the idea of a per-clip tailoring of parameters for op…
Energy-Rate-Quality Tradeoffs of State-of-the-Art Video Codecs
Angeliki Katsenou, Jongwewi Mao, Ioannis Mavromatis
The adoption of video conferencing and video communication services, accelerated by COVID-19, has driven a rapid increase in video data traffic. The demand for higher resolutions a…
Direct Optimisation of for HDR Content Adaptive Transcoding in AV1
Vibhoothi, François Pitié, Angeliki Katsenou +6
Since the adoption of VP9 by Netflix in 2016, royalty-free coding standards continued to gain prominence through the activities of the AOMedia consortium. AV1, the latest open sour…
A CNN-based Post-Processor for Perceptually-Optimized Immersive Media Compression
Angeliki Katsenou, Fan Zhang, David Bull
In recent years, resolution adaptation based on deep neural networks has enabled significant performance gains for conventional (2D) video codecs. This paper investigates the effec…
VMAF-based Bitrate Ladder Estimation for Adaptive Streaming
Angeliki V. Katsenou, Fan Zhang, Kyle Swanson +3
In HTTP Adaptive Streaming, video content is conventionally encoded by adapting its spatial resolution and quantization level to best match the prevailing network state and display…
Enhancing VMAF through New Feature Integration and Model Combination
Fan Zhang, Angeliki Katsenou, Christos Bampis +3
VMAF is a machine learning based video quality assessment method, originally designed for streaming applications, which combines multiple quality metrics and video features through…
Efficient Bitrate Ladder Construction for Content-Optimized Adaptive Video Streaming
Angeliki V. Katsenou, Joel Sole, David R. Bull
One of the challenges faced by many video providers is the heterogeneity of network specifications, user requirements, and content compression performance. The universal solution o…
Study of Compression Statistics and Prediction of Rate-Distortion Curves for Video Texture
Angeliki V. Katsenou, Mariana Afonso, David R. Bull
Encoding textural content remains a challenge for current standardised video codecs. It is therefore beneficial to understand video textures in terms of both their spatio-temporal…
Encoding in the Dark Grand Challenge: An Overview
Nantheera Anantrasirichai, Fan Zhang, Alexandra Malyugina +2
A big part of the video content we consume from video providers consists of genres featuring low-light aesthetics. Low light sequences have special characteristics, such as spatio-…