most citedTowards a Robust Framework for NeRF Evaluation

4 citations · 4 across the 6 of their papers we have counts for

collaborators

6 papers

eess.IV2024

BVI-UGC: A Video Quality Database for User-Generated Content Transcoding

Zihao Qi, Chen Feng, Fan Zhang +3

In recent years, user-generated content (UGC) has become one of the major video types consumed via streaming networks. Numerous research contributions have focused on assessing its…

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…

eess.IV2023

Wavelet-based Topological Loss for Low-Light Image Denoising

Alexandra Malyugina, Nantheera Anantrasirichai, David Bull

Despite extensive research conducted in the field of image denoising, many algorithms still heavily depend on supervised learning and their effectiveness primarily relies on the qu…

cs.CV2023

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…

cs.CV20234 cited

Towards a Robust Framework for NeRF Evaluation

Adrian Azzarelli, Nantheera Anantrasirichai, David R Bull

Neural Radiance Field (NeRF) research has attracted significant attention recently, with 3D modelling, virtual/augmented reality, and visual effects driving its application. While…

eess.IV2023

ST-MFNet Mini: Knowledge Distillation-Driven Frame Interpolation

Crispian Morris, Duolikun Danier, Fan Zhang +2

Currently, one of the major challenges in deep learning-based video frame interpolation (VFI) is the large model sizes and high computational complexity associated with many high p…