26 citations · 58 across the 23 of their papers we have counts for
10 papers · 1 filter
Exploring Dynamic Novel View Synthesis Technologies for Cinematography
Adrian Azzarelli, Nantheera Anantrasirichai, David R Bull
Novel view synthesis (NVS) has shown significant promise for applications in cinematographic production, particularly through the exploitation of Neural Radiance Fields (NeRF) and…
BVI-CR: A Multi-View Human Dataset for Volumetric Video Compression
Ge Gao, Adrian Azzarelli, Ho Man Kwan +4
The advances in immersive technologies and 3D reconstruction have enabled the creation of digital replicas of real-world objects and environments with fine details. These processes…
UW-GS: Distractor-Aware 3D Gaussian Splatting for Enhanced Underwater Scene Reconstruction
Haoran Wang, Nantheera Anantrasirichai, Fan Zhang +1
3D Gaussian splatting (3DGS) offers the capability to achieve real-time high quality 3D scene rendering. However, 3DGS assumes that the scene is in a clear medium environment and s…
Deep Learning Techniques for Atmospheric Turbulence Removal: A Review
Paul Hill, Nantheera Anantrasirichai, Alin Achim +1
The influence of atmospheric turbulence on acquired imagery makes image interpretation and scene analysis extremely difficult and reduces the effectiveness of conventional approach…
BVI-RLV: A Fully Registered Dataset for Low-Light Video Enhancement
Ruirui Lin, Guoxi Huang, Joanne Lin +4
Low-light videos often exhibit spatiotemporally incoherent noise, compromising visibility and degrading performance in computer vision applications. A major challenge for enhancing…
DaBiT: Depth and Blur informed Transformer for Video Focal Deblurring
Crispian Morris, Nantheera Anantrasirichai, Fan Zhang +1
In many real-world scenarios, recorded videos suffer from accidental focus blur, and while video deblurring methods exist, most specifically target motion blur or spatial-invariant…
Reviewing Intelligent Cinematography: AI research for camera-based video production
Adrian Azzarelli, Nantheera Anantrasirichai, David R Bull
This paper offers the first comprehensive review of artificial intelligence (AI) research in the context of real camera content acquisition for entertainment purposes and is aimed…
A Spatio-temporal Aligned SUNet Model for Low-light Video Enhancement
Ruirui Lin, Nantheera Anantrasirichai, Alexandra Malyugina +1
Distortions caused by low-light conditions are not only visually unpleasant but also degrade the performance of computer vision tasks. The restoration and enhancement have proven t…
Multi-Scale Denoising in the Feature Space for Low-Light Instance Segmentation
Joanne Lin, Nantheera Anantrasirichai, David Bull
Instance segmentation for low-light imagery remains largely unexplored due to the challenges imposed by such conditions, for example shot noise due to low photon count, color disto…
BVI-Lowlight: Fully Registered Benchmark Dataset for Low-Light Video Enhancement
Nantheera Anantrasirichai, Ruirui Lin, Alexandra Malyugina +1
Low-light videos often exhibit spatiotemporal incoherent noise, leading to poor visibility and compromised performance across various computer vision applications. One significant…