1 code implementation • 16 Feb 2023 • Crispian Morris, Duolikun Danier, Fan Zhang, Nantheera Anantrasirichai, David R. Bull
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 performance VFI approaches.
no code implementations • 15 Jun 2021 • Di Ma, Mariana Afonso, Fan Zhang, David R. Bull
Spatial resolution adaptation is a technique which has often been employed in video compression to enhance coding efficiency.
no code implementations • 15 Jun 2021 • Fan Zhang, David R. Bull
This paper describes an adaptive Lagrange multiplier determination method for rate-quality optimisation in video compression.
no code implementations • 15 Jun 2021 • 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 adaptive combination of noticeable distortions and blurring artefacts.
no code implementations • 12 Mar 2021 • Angeliki V. Katsenou, Fan Zhang, Kyle Swanson, Mariana Afonso, Joel Sole, David R. Bull
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 characteristics.
1 code implementation • 18 Nov 2020 • Di Ma, Fan Zhang, David R. Bull
We propose a new Generative Adversarial Network for Compressed Video quality Enhancement (CVEGAN).
no code implementations • 16 Sep 2020 • Fan Zhang, Di Ma, Chen Feng, David R. Bull
In recent years, video compression techniques have been significantly challenged by the rapidly increased demands associated with high quality and immersive video content.
no code implementations • 29 Jul 2020 • 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 before encoding and super-resolving at the decoder.
no code implementations • 14 Jul 2020 • Di Ma, Fan Zhang, David R. Bull
Each MFRB extracts features from multiple convolutional layers using dense connections and a multi-level residual learning structure.
no code implementations • 30 Mar 2020 • 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 conventional approaches.
no code implementations • 23 Mar 2020 • Angeliki V. Katsenou, Fan Zhang, Mariana Afonso, Goce Dimitrov, David R. Bull
The compression efficiency of the codecs was evaluated with commonly used objective quality metrics, and the subjective quality of their reconstructed content was also evaluated through psychophysical experiments.
1 code implementation • 14 Mar 2020 • Nantheera Anantrasirichai, Majid Geravand, David Braendler, David R. Bull
Disparity/depth estimation from sequences of stereo images is an important element in 3D vision.
no code implementations • 7 Nov 2019 • Fan Zhang, Mariana Afonso, David R. Bull
Our results show consistent and significant compression gains against HM and VVC based on Bj{\o}negaard Delta measurements, with average BD-rate savings of 12. 6% (PSNR) and 19. 5% (VMAF) over HM and 5. 5% (PSNR) and 8. 6% (VMAF) over VTM.
no code implementations • 13 Nov 2017 • Alexander B. Tibbs, Ilse M. Daly, Nicholas W. Roberts, David R. Bull
Imaging polarimetry allows more information to be extracted from a scene than conventional intensity or colour imaging.