162 citations · 433 across the 16 of their papers we have counts for
16 papers
DTKDP: A Dual Teacher Knowledge Distillation and Pruning Framework for Lightweight Oriented SAR Ship Detection
Yuming Li, Fan Zhang, Alin M. Achim
Two-stage oriented detectors achieve high localization accuracy in synthetic aperture radar (SAR) ship detection, but their large backbones, feature pyramids, proposal modules, and…
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…
RankDVQA: Deep VQA based on Ranking-inspired Hybrid Training
Chen Feng, Duolikun Danier, Fan Zhang +1
In recent years, deep learning techniques have shown significant potential for improving video quality assessment (VQA), achieving higher correlation with subjective opinions compa…
ViSTRA3: Video Coding with Deep Parameter Adaptation and Post Processing
Chen Feng, Duolikun Danier, Charlie Tan +2
This paper presents a deep learning-based video compression framework (ViSTRA3). The proposed framework intelligently adapts video format parameters of the input video before encod…
Perceptually-inspired super-resolution of compressed videos
Di Ma, Mariana Afonso, Fan Zhang +1
Spatial resolution adaptation is a technique which has often been employed in video compression to enhance coding efficiency. This approach encodes a lower resolution version of th…
An adaptive Lagrange multiplier determination method for rate-distortion optimisation in hybrid video codecs
Fan Zhang, David R. Bull
This paper describes an adaptive Lagrange multiplier determination method for rate-quality optimisation in video compression. Inspired by the experimental results of a Lagrange mul…
Quality assessment methods for perceptual video compression
Fan Zhang, David R. Bull
This paper describes a quality assessment model for perceptual video compression applications (PVM), which stimulates visual masking and distortion-artefact perception using an ada…
A Subjective Study on Videos at Various Bit Depths
Alex Mackin, Di Ma, Fan Zhang +1
Bit depth adaptation, where the bit depth of a video sequence is reduced before transmission and up-sampled during display, can potentially reduce data rates with limited impact on…
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…
CVEGAN: A Perceptually-inspired GAN for Compressed Video Enhancement
Di Ma, Fan Zhang, David R. Bull
We propose a new Generative Adversarial Network for Compressed Video quality Enhancement (CVEGAN). The CVEGAN generator benefits from the use of a novel Mul2Res block (with multipl…
Video Compression with CNN-based Post Processing
Fan Zhang, Di Ma, Chen Feng +1
In recent years, video compression techniques have been significantly challenged by the rapidly increased demands associated with high quality and immersive video content. Among va…
Video compression with low complexity CNN-based spatial resolution adaptation
Di Ma, Fan Zhang, David R. Bull
It has recently been demonstrated that spatial resolution adaptation can be integrated within video compression to improve overall coding performance by spatially down-sampling bef…
MFRNet: A New CNN Architecture for Post-Processing and In-loop Filtering
Di Ma, Fan Zhang, David R. Bull
In this paper, we propose a novel convolutional neural network (CNN) architecture, MFRNet, for post-processing (PP) and in-loop filtering (ILF) in the context of video compression.…
BVI-DVC: A Training Database for Deep Video Compression
Di Ma, Fan Zhang, David R. Bull
Deep learning methods are increasingly being applied in the optimisation of video compression algorithms and can achieve significantly enhanced coding gains, compared to convention…
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…
ViSTRA2: Video Coding using Spatial Resolution and Effective Bit Depth Adaptation
Fan Zhang, Mariana Afonso, David R. Bull
We present a new video compression framework (ViSTRA2) which exploits adaptation of spatial resolution and effective bit depth, down-sampling these parameters at the encoder based…