26 citations · 58 across the 23 of their papers we have counts for
28 papers
Separation of variables for coupled radiative perturbations of Kerr-Newman-de Sitter black holes
Daisuke Yoshida
We extend Hintz's separation of variables for radiative gravitational and electromagnetic perturbations from Kerr-Newman to Kerr-Newman-de Sitter black holes. On subextremal backgr…
OceanXL: Large-scale Underwater 3D Gaussian Splatting via Block Partitioning and Adaptive Pruning
Haoran Wang, Shaoyu Cai, Adrian Azzarelli +7
Underwater 3D reconstruction is critical for marine exploration, ecological monitoring, and subsea infrastructure inspection, yet remains challenging at large scale due to light at…
FGSVQA: Frequency-Guided Short-form Video Quality Assessment
Xinyi Wang, Angeliki Katsenou, Junxiao Shen +1
Short-form video poses new challenges to the quality assessment of user-generated content (UGC) due to its complex generation pipeline, rapid content variation, and mixed distortio…
Relightable Gaussian Splatting for Virtual Production Using Image-Based Illumination
Adrian Azzarelli, Nantheera Anantrasirichai, James Pollock +1
Virtual production (VP) use LED walls to provide both background imagery and image-based lighting. While this enables on-set compositing, it couples lighting to background and scen…
PixIE: Prompted Pixel-Space Low-Light Image Enhancement
Ruirui Lin, Guoxi Huang, David Bull +1
Low-light images suffer from severe noise, contrast loss, and semantic ambiguity, making enhancement a joint problem of denoising and detail recovery. We propose PixIE, a feed-forw…
BVI-Mamba: Video Enhancement Using a Visual State-Space Model for Low-Light and Underwater Environments
Guoxi Huang, Ruirui Lin, Yini Li +2
Videos captured in low-light and underwater conditions often suffer from distortions such as noise, low contrast, color imbalance, and blur. These issues not only limit visibility…
Prune Wisely, Reconstruct Sharply: Compact 3D Gaussian Splatting via Adaptive Pruning and Difference-of-Gaussian Primitives
Haoran Wang, Guoxi Huang, Fan Zhang +2
Recent significant advances in 3D scene representation have been driven by 3D Gaussian Splatting (3DGS), which has enabled real-time rendering with photorealistic quality. 3DGS oft…
PocketDVDNet: Realtime Video Denoising for Real Camera Noise
Crispian Morris, Imogen Dexter, Fan Zhang +2
Live video denoising under realistic, multi-component sensor noise remains challenging for applications such as autofocus, autonomous driving, and surveillance. We propose PocketDV…
ELVIS: Enhance Low-Light for Video Instance Segmentation in the Dark
Joanne Lin, Ruirui Lin, Yini Li +2
Video instance segmentation (VIS) for low-light content remains highly challenging for both humans and machines alike, due to noise, blur and other adverse conditions. The lack of…
TempRetinex: Retinex-based Unsupervised Enhancement for Low-light Video Under Diverse Lighting Conditions
Yini Li, Louis Forster, David Bull +1
The acquisition of paired low-light video sequences remains challenging due to issues associated with poor temporal consistency, varying illumination characteristics and camera par…
Splatography: Sparse multi-view dynamic Gaussian Splatting for filmmaking challenges
Adrian Azzarelli, Nantheera Anantrasirichai, David R Bull
Deformable Gaussian Splatting (GS) accomplishes photorealistic dynamic 3-D reconstruction from dense multi-view video (MVV) by learning to deform a canonical GS representation. How…
From Restoration to Reconstruction: Rethinking 3D Gaussian Splatting for Underwater Scenes
Guoxi Huang, Haoran Wang, Zipeng Qi +3
Underwater image degradation poses significant challenges for 3D reconstruction, where simplified physical models often fail in complex scenes. We propose \textbf{R-Splatting}, a u…
DMAT: An End-to-End Framework for Joint Atmospheric Turbulence Mitigation and Object Detection
Paul Hill, Zhiming Liu, Alin Achim +2
Atmospheric Turbulence (AT) degrades the clarity and accuracy of surveillance imagery, posing challenges not only for visualization quality but also for object classification and s…
Towards a General-Purpose Zero-Shot Synthetic Low-Light Image and Video Pipeline
Joanne Lin, Crispian Morris, Ruirui Lin +3
Low-light conditions pose significant challenges for both human and machine annotation. This in turn has led to a lack of research into machine understanding for low-light images a…
Bayesian Neural Networks for One-to-Many Mapping in Image Enhancement
Guoxi Huang, Qirui Yang, Ruirui Lin +3
In image enhancement tasks, such as low-light and underwater image enhancement, a degraded image can correspond to multiple plausible target images due to dynamic photography condi…
Advances in Artificial Intelligence: A Review for the Creative Industries
Nantheera Anantrasirichai, Fan Zhang, David Bull
Artificial intelligence (AI) has undergone transformative advances since 2022, particularly through generative AI, large language models (LLMs), and diffusion models, fundamentally…
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…