activity
20232026
most citedReviewing Intelligent Cinematography: AI research for camera-based video production

26 citations · 35 across the 9 of their papers we have counts for

collaborators

10 papers

cs.CV2026

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…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

ViVo: A Dataset for Volumetric Video Reconstruction and Compression

Adrian Azzarelli, Ge Gao, Ho Man Kwan +4

As research on neural volumetric video reconstruction and compression flourishes, there is a need for diverse and realistic datasets, which can be used to develop and validate reco…

cs.CV2025★ 3 cited

AquaNeRF: Neural Radiance Fields in Underwater Media with Distractor Removal

Luca Gough, Adrian Azzarelli, Fan Zhang +1

Neural radiance field (NeRF) research has made significant progress in modeling static video content captured in the wild. However, current models and rendering processes rarely co…

cs.CV2024

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…

cs.CV2024★ 1 cited

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…

cs.CV2024★ 26 cited

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…

cs.CV2023★ 1 cited

WavePlanes: Compact Hex Planes for Dynamic Novel View Synthesis

Adrian Azzarelli, Nantheera Anantrasirichai, David R Bull

Dynamic Novel View Synthesis (Dynamic NVS) enhances NVS technologies to model moving 3-D scenes. However, current methods are resource intensive and challenging to compress. To add…

cs.CV2023★ 4 cited

Towards a Robust Framework for NeRF Evaluation

Adrian Azzarelli, Nantheera Anantrasirichai, David R Bull

Neural Radiance Field (NeRF) research has attracted significant attention recently, with 3D modelling, virtual/augmented reality, and visual effects driving its application. While…