Dr Nantheera Anantrasirichai (Pui)

Associate Professor in Visual Computing

3.20, Merchant Venturers Building, University of Bristol

Bristol, BS8 1UB, UK

eexna*at*bris.ac.uk

About

I am an Associate Professor in the School of Computer Science at the University of Bristol (UoB) and a member of the Visual Information Laboratory, led by Prof. Alin Achim, and the Bristol Vision Institute, led by Prof. David Bull. I have been involved in many projects across multiple disciplines, including telecommunications, biology, optometry, clinical sciences, biochemistry, mechanical engineering, psychology and geoscience. I lead a work package, AI Workflows for Challenging Acquisition Environments, as part of MyWorld, strengthening the world-leading position of creative technologies in the southwest region. Additionally, I am a key scientist at the Centre for the Observation and Modelling of Earthquakes, Volcanoes, and Tectonics (COMET).

I am a Programme Director of MSc Immersive Technologies (Virtual and Augmented Reality). During the 2024/2025 academic year, I will be on a University Research Fellowship and therefore will not be involved in teaching. For any inquiries regarding Image Processing and Computer Vision (Y3), Advanced Visual AI (Y4), and Immersive Interaction and Audio Design (PGT), please contact the respective Unit Directors.

Opportunities

Senior Research Associate funded by EPSRC: Project 'Intelligent Video Restoration and Enhancement via a Large Prior Database'
PhD Scholarship funded by UoB/EPSRC: Project 'Intelligent Video Restoration and Enhancement via a Large Prior Database'
PhD Scholarship funded by UoB: University of Bristol Postgraduate Research Scholarships. Please send me your CV and transcripts.

Research Interests

Image and video analysis
Image and video enhancement
Object detection and tracking
3D representation
Machine learning
Inverse problem
Remote sensing
Medical imaging

Highlights

UW-GS: Distractor-Aware 3D Gaussian Splatting for Enhanced Underwater Scene Reconstruction and DaBiT: Depth and blur informed transformer for video deblurring are presenting at WACV2025
Low-light Video Enhancement with Conditional Diffusion Models and Wavelet Interscale Attentions won the best paper award at ACM SIGGRAPH CVMP
BVI-Lowlight: Fully registered datasets for low-light image and video enhancement
Updated review paper: Artificial Intelligence in Creative Industries: Advances Prior to 2025

News & Activities

2025-2027: EURASIP TAC (Second Term) Biomedical Image & Signal Analytics
29 April 2025: Invited talk: EGU
12 Mar 2024: Invited talk: AI for Visual Data at CenSoF
12 Feb 2024: New project! MyUnderwaterWorld
31 Oct 2023: New dataset! BVI-Lowlight Fully registered video dataset
5 Oct 2023: Invited speaker at Bringing Space Down to Earth
1 Jun 2023: New project! Object recognition under heat haze environment
1 Mar 2023: Invited talk AI-based Image Processing for Challenging Natural Data

Previous News & Activities: see here

BVI-Lowlight datasets

Projects

Production Workflow for Challenging Environments

Medical and Biological Image Computing

Deep Learning for Computational Microscopy

Computational Imaging in Remote Sensing

Computer Vision for Robotics

More projects and details: see here

Publications

For all my papers, see both google scholar and university site

Selected papers

Feature Denoising For Low-Light Instance Segmentation Using Weighted Non-Local Blocks. J Lin, N Anantrasirichai, D Bull, ICASSP 2025 [PDF]
UW-GS: Distractor-Aware 3D Gaussian Splatting for Enhanced Underwater Scene Reconstruction. H Wang, N Anantrasirichai, F Zhang, D Bull, WACV 2025 [PDF] [Code] [Project]
DeTurb: Atmospheric Turbulence Mitigation with Deformable 3D Convolutions and 3D Swin Transformers. Z Zou, N Anantrasirichai, ACCV 2024 [PDF] [Code] [Project]
TaGAT: Topology-Aware Graph Attention Network For Multi-modal Retinal Image Fusion. X Tian, N Anantrasirichai, L Nicholson, A Achim. MICCAI 2024 [PDF] [Code] [Dataset] [Project]
Learning Ground Displacement Signals Directly from InSAR-Wrapped Interferograms. L Moualla, A Rucci, G Naletto, N Anantrasirichai. Sensors. 2024 [PDF]
Parasitic Egg Detection and Classification in Low-cost Microscopic Images using Transfer Learning. T Suwannaphong, S Chavana, S Tongsom, D Palasuwan, T H Chalidabhongse, and N Anantrasirichai. SN Computer Science. 2023 [PDF] [Dataset]
Current Advances in Computational Lung Ultrasound Imaging: A Review. T. Yang, O. Karakuş, N. Anantrasirichai, and A. Achim. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control. 2023.[PDF]
ICIP 2022 Challenge on Parasitic Egg Detection and Classification in Microscopic Images: Dataset, Methods and Results. N Anantrasirichai, TH Chalidabhongse, D Palasuwan, K Naruenatthanaset, T Kobchaisawat, N Nunthanasup, K Boonpeng, X Ma, and A Achim. IEEE International Conference on Image Processing. 2022. [PDF] [Dataset] [Website]
Detecting Ground Deformation in the Built Environment using Sparse Satellite InSAR data with a Convolutional Neural Network. N. Anantrasirichai, J. Biggs, K. Kelevitz, Z. Sadeghi, T. Wright, J. Thompson, A. Achim and D. Bull. IEEE Transactions on Geoscience and Remote Sensing. 2020.[PDF] [Project]
Image fusion via sparse regularization with non-convex penalties. N. Anantrasirichai, R. Zheng, I. Selesnick and A. Achim. Pattern Recognition Letters. 2020. [PDF] [CODE]
River Planform Extraction From High-Resolution SAR Images Via Generalised Gamma Distribution Superpixel Classification. O. Pappas, N. Anantrasirichai, A. Achim and B. Adams. IEEE Transactions on Geoscience and Remote Sensing. 2020.[PDF]
Detection of Line Artefacts in Lung Ultrasound Images of COVID-19 Patients via Non-Convex Regularization. O. Karakuş, N. Anantrasirichai, A. Aguersif, S. Silva, A. Basarab and A Achim. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control. 2020.[PDF] [BibTeX] [CODE]
The Application of Convolutional Neural Networks to Detect Slow, Sustained Deformation in InSAR Timeseries. N. Anantrasirichai, J. Biggs, F. Albino, and David Bull. Geophysical Research Letters. 2019. [PDF] [BibTeX] [Project]
A Deep Learning Approach to Detecting Volcano Deformation from Satellite Imagery using Synthetic Datasets. N. Anantrasirichai, J. Biggs, F. Albino, and David Bull. Remote Sensing of Environment. 2019. [PDF] [BibTeX] [CODE] [Project]

More papers: see here

Download

Datasets

BVI-RLV: Fully Registered Low-Light Videos
BVI-LOWLIGHT: Dataset for Low-Light Image Denoising [Paper]
BVI-Turb: Atmospheric Turbulence Dataset
BVI-Coral: Underwater scenes for 3D reconstruction [Paper]
OCT2Confocal: in-vivo OCT and ex-vivo confocal retinal images [Paper]
ICIP 2022 Challenge: Parasitic Egg Detection and Classification in Microscopic Images [Paper]
Chula-parasitic-eggs: Parasitic Egg Detection and Classification in Low-cost Microscopic Images [Paper]
LICS Dataset for Volcanic Deformation Classification [Paper]

Find more code and datasets here.