1.3k citations · 1.5k across the 18 of their papers we have counts for
9 papers · 1 filter
HiNeRV: Video Compression with Hierarchical Encoding-based Neural Representation
Ho Man Kwan, Ge Gao, Fan Zhang +2
Learning-based video compression is currently a popular research topic, offering the potential to compete with conventional standard video codecs. In this context, Implicit Neural…
LDMVFI: Video Frame Interpolation with Latent Diffusion Models
Duolikun Danier, Fan Zhang, David Bull
Existing works on video frame interpolation (VFI) mostly employ deep neural networks that are trained by minimizing the L1, L2, or deep feature space distance (e.g. VGG loss) betwe…
BVI-VFI: A Video Quality Database for Video Frame Interpolation
Duolikun Danier, Fan Zhang, David Bull
Video frame interpolation (VFI) is a fundamental research topic in video processing, which is currently attracting increased attention across the research community. While the deve…
Enhancing HDR Video Compression through CNN-based Effective Bit Depth Adaptation
Chen Feng, Zihao Qi, Duolikun Danier +4
It is well known that high dynamic range (HDR) video can provide more immersive visual experiences compared to conventional standard dynamic range content. However, HDR content is…
FloLPIPS: A Bespoke Video Quality Metric for Frame Interpoation
Duolikun Danier, Fan Zhang, David Bull
Video frame interpolation (VFI) serves as a useful tool for many video processing applications. Recently, it has also been applied in the video compression domain for enhancing bot…
Enhancing VVC with Deep Learning based Multi-Frame Post-Processing
Duolikun Danier, Chen Feng, Fan Zhang +1
This paper describes a CNN-based multi-frame post-processing approach based on a perceptually-inspired Generative Adversarial Network architecture, CVEGAN. This method has been int…
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…
A Subjective Quality Study for Video Frame Interpolation
Duolikun Danier, Fan Zhang, David Bull
Video frame interpolation (VFI) is one of the fundamental research areas in video processing and there has been extensive research on novel and enhanced interpolation algorithms. T…
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…