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Majid Mirmehdi

Prof. Majid Mirmehdi

Professor of Computer Vision

Fellow IAPR, BMVA Distinguished Fellow

Machine Learning and Computer Vision
Department of Computer Science
University of Bristol
Merchant Venturers Building
Woodland Road, Bristol BS8 1UB, UK
Tel: +44 (0)117-455 8158
Email: M.Mirmehdi@cs.bris.ac.uk
ORCID:0000-0002-6478-1403

IAPR Fellow

SPHERE | PD Sensors | Wilddrone

Selection of Publications

Use Your Head: Improving Long-Tail Video Recognition. T Perrett, S Sinha, T Burghardt, M Mirmehdi, D Damen. CVPR 2023
Paper and Code
TranSOP: Transformer-based Multimodal Classification for Stroke Treatment Outcome Prediction. Z Samak, P. Clatworthy, M. Mirmehdi 20th IEEE International Symposium on Biomedical Imaging. ISBI 2023
Paper and Code
Triple-stream Deep Metric Learning of Great Ape Behavioural Actions. O Brookes, M Mirmehdi, H Kuehl, T Burghardt. VISAPP 2023.
Paper and Code
Dynamic Curriculum Learning for Great Ape Detection in the Wild. X. Yang, T. Burghardt, M. Mirmehdi. International Journal of Computer Vision (IJCV), 2023.
Paper and Code
Video-SwinUNet: Spatio-temporal Deep Learning Framework for VFSS Instance Segmentation. Zeng, X Yang, D Smithard, M Mirmehdi, AM Gambaruto, T Burghardt. ICIP2023
(Arxiv PDF), (GitHub)
FeMA: Feature matching auto-encoder for predicting ischaemic stroke evolution and treatment outcome. Z Samak, P. Clatworthy, M. Mirmehdi Computerized Medical Imaging and Graphics, 2022
Paper | Code
Refining Action Boundaries for One-Stage Detection. H Wang, M Mirmehdi, D Damen, T Perrett. AVSS 2022
Paper and Code
Personalised Energy Expenditure Estimation: A Visual Sensing Approach With Deep Learning. T Perrett, A Masullo, D Damen, T Burghardt, I Craddock, M Mirmehdi. JMIR Formative Research 2022
Paper
Small or Far Away? Exploiting Deep Super-Resolution and Altitude Data for Aerial Animal Surveillance. M Xue, T Greenslade, M. Mirmehdi and T. Burghardt. WACV Workshop (RWS) 2022.
Paper
No Need for a Lab: Towards Multi-Sensory Fusion for Ambient Assisted Living in Real-World Living Homes. A Masullo, TJ Perrett, D Damen, T Burghardt, M Mirmehdi. VISAPP 2021
Paper
Back to the Future: Cycle Encoding Prediction for Self-supervised Video Representation Learning. X. Yang, M. Mirmehdi and T. Burghardt, BMVC (2021).
Paper and Code
Unsupervised View-Invariant Human Posture Representation. F. Sardari, B. Ommer, and M. Mirmehdi, BMVC (2021).
Paper and Code
Temporal-Relational CrossTransformers for Few-Shot Action Recognition. T Perrett, A Masullo, T Burghardt, M Mirmehdi, D Damen. CVPR (2021).
ArXiv | Project Webpage | Code and Model
Person Re-ID by Fusion of Video Silhouettes and Wearable Signals for Home Monitoring Applications. A Masullo, T Burghardt, D Damen, T Perrett, M Mirmehdi. Sensors 20(9) 2020.
HTML | PDF

Meta-Learning with Context-Agnostic Initialisation. T Perrett, A Masullo, T Burghard, M Mirmehdi, D Damen. ACCV 2020.
CVF | CVF PDF | Project Page | Talk Video

VI-Net: View-Invariant Quality of Human Movement Assessment. F Sardari, A Paiement, S Hannuna, M Mirmehdi. Sensors 20(18) 2020.
HTML | PDF

Prediction of Thrombectomy Functional Outcomes using Multimodal Data, Z Samak, P. Clatworthy, M. Mirmehdi MIUA 2020.
Springer Link | arXive
Who Goes There? Exploiting Silhouettes and Wearable Signals for Subject Identification in Multi-Person Environments, A Masullo, T Burghardt, D Damen, T Perrett, M Mirmehdi. 2nd Int. Workshop on Computer Vision for Physiological Measurement (CVPM) at IEEE International Conference of Computer Vision (ICCVW), 2019.
CVF Version | Dataset: SPHERE-Calorie
Analysing Cooking Behaviour in Home Settings: Towards Health Monitoring. K Yordanova, S Ludtke, S Whitehouse, F Kruger, A Paiement, M Mirmehdi, I Craddock, T Kirste. Sensors, 19(3), 646, 2019
Link to PDF

What is cooking and Why? Behaviour Recognition during Unscripted Cooking Tasks for Health Monitoring. K Yordanova, S Whitehouse, A Paiement, M Mirmehdi, T Kirste, I Craddock. PerCom 2017 (Best work in progress paper award)
Link to PDF | Dataset: SPHERE Unscripted kitchen activities
Great Ape Detection in Challenging Jungle Camera Trap Footage via Attention-Based Spatial and Temporal Feature Blending, X. Yang, M. Mirmehdi, T. Burghardt, Computer Vision for Wildlife Conservation (CVWC) Workshop at IEEE International Conference of Computer Vision (ICCVW) , 2019.
CVF Version | Arxiv PDF | Dataset PanAfrican2019 Video | Dataset: PanAfrican2019 Annotations and Code
Weakly-Supervised Completion Moment Detection using Temporal Attention. F Heidarivincheh, M Mirmehdi, D Damen. ICCV Workshop on Human Behaviour Understanding, 2019
Arxiv PDF | CVF PDF

Action Completion: A Temporal Model for Moment Detection. F Heidarivincheh, M Mirmehdi, D Damen. BMVC, 2018
Arxiv PDF | Video2018 | Dataset

Beyond Action Recognition: Action Completion in RGB-D Data. F Heidarivincheh, M Mirmehdi, D Damen. BMVC, 2016
pdf | abstract | Video2016 | Dataset: RGBD-Action-Completion-2016
CaloriNet: From silhouettes to calorie estimation in private environments. A Masullo, T Burghardt, D Damen, S Hannuna, V Ponce-Lopez, M Mirmehdi, BMVC 2018
PDF | Code on Github

Energy expenditure estimation using visual and inertial sensors. L Tao, T Burghardt, M Mirmehdi, D Damen, A. Cooper, S. Hannuna, M Camplani, A. Paiement, I Craddock. IET Computer Vision, 12(1), 2018.
OA PDF @IET | SPHERE Webpage
3D Data Acquisition and Registration using Two Opposing Kinects. V Soleimani, M Mirmehdi, D Damen, S Hannuna, M Camplani, 4th International Conference on 3D Vision (3DV), 128-137, 2016
PDF@ieeexplore | Code
Real-time RGB-D Tracking with Depth Scaling Kernelised Correlation Filters and Occlusion Handling. M Camplani, S Hannuna, M Mirmehdi, D Damen, L Tao, T Burghardt and A Paiment. British Machine Vision Conference (BMVC), Sep 2015.
PDF | Video 1 | Video 2 | Code on Github
Online quality assessment of human movement from skeleton data. A Paiment, L Tao, S Hannuna, M Camplani, D Damen and M Mirmehdi. British Machine Vision Conference (BMVC), Sep 2014.
PDF | Dataset | Code

Handbook of Texture Analysis

Handbook of Texture Analysis
Collection of chapters on many aspects of texture analysis (pre-deep learning era!)
Hardcover: 424 pages - Publisher: Imperial College Press (Dec. 2008) - ISBN-13: 978-1848161153
Sample chapter: A Galaxy of Texture Features

Last Updated Feb. 2020