I am a Lecturer (roughly equivalent to Assistant Professor) in Machine Learning at the University of Glasgow. My research focuses on building machines that understand the visual world with minimal supervision, learning aspects of its structure such as 3D geometry and decomposition into objects. This work lies at the intersection of machine learning, computer vision, and computer graphics. I also work on applications of machine learning and computer vision in the physical and life sciences.

Prospective PhD students: I am currently accepting PhD students to supervise. There are studentships available for strong candidates. Please first check that your research interests align with mine (read this page; read some of my papers). If so, send me an email with your CV, transcripts and a short research proposal (2–3 pages) mentioning why you want to work in my group in particular, and what skills make you suited. Note that I expect students to produce at least two 'good' papers during their PhD (CVPR, NeurIPS, etc.). Applicants should have a strong background in coding and maths (e.g. probability, linear algebra).

Research
RenderDiffusion: Image Diffusion for 3D Reconstruction, Inpainting and Generation
Titas Anciukevičius, Zexiang Xu, Matthew Fisher, Paul Henderson, Hakan Bilen, Niloy J. Mitra and Paul Guerrero
CVPR 2023  (new!)
Simulating analogue film damage to analyse and improve artefact restoration on high-resolution scans
Daniela Ivanova, John Williamson and Paul Henderson
Eurographics 2023 / Computer Graphics Forum  (new!)
Unsupervised Causal Generative Understanding of Images
Titas Anciukevicius, Patrick Fox-Roberts, Edward Rosten and Paul Henderson
NeurIPS 2022
Determining band structure parameters of two-dimensional materials by deep learning
Paul Henderson, Areg Ghazaryan, Alexander A. Zibrov, Andrea F. Young and Maksym Serbyn
arXiv 2022
Learning to Predict Keypoints and Structure of Articulated Objects without Supervision
Titas Anciukevicius, Paul Henderson and Hakan Bilen
ICPR 2022
Unsupervised Video Prediction from a Single Frame by Estimating 3D Dynamic Scene Structure
Paul Henderson, Christoph Lampert and Bernd Bickel
CoRR 2021
Unsupervised object-centric video generation and decomposition in 3D
Paul Henderson and Christoph Lampert
NeurIPS 2020
Computational Design of Cold Bent Glass Façades
Konstantinos Gavriil, Ruslan Guseinov, Jesús Pérez, Davide Pellis, Paul Henderson, Florian Rist, Helmut Pottmann and Bernd Bickel
SIGGRAPH Asia 2020
Leveraging 2D Data to Learn Textured 3D Mesh Generation
Paul Henderson, Vagia Tsiminaki and Christoph Lampert
CVPR 2020 (oral)
Object-Centric Image Generation with Factored Depths, Locations, and Appearances
Titas Anciukevicius, Christoph Lampert and Paul Henderson
CoRR 2020
Learning Single-Image 3D Reconstruction by Generative Modelling of Shape, Pose and Shading
Paul Henderson and Vittorio Ferrari
IJCV 2019
Learning to Generate and Reconstruct 3D Meshes with only 2D Supervision
Paul Henderson and Vittorio Ferrari
BMVC 2018 (oral)
Automatic Generation of Constrained Furniture Layouts
Paul Henderson, Kartic Subr and Vittorio Ferrari
CoRR 2017
End-to-end Training of Object Class Detectors for Mean Average Precision
Paul Henderson and Vittorio Ferrari
ACCV 2016
Automatically Selecting Inference Algorithms for Discrete Energy Minimisation
Paul Henderson and Vittorio Ferrari
ECCV 2016
Profile

I completed a BA in Mathematics at the University of Cambridge in 2009, followed by an MSc in Informatics at the University of Edinburgh in 2010. I then worked at Blackford Analysis for four years, on research and development for medical imaging applications. I completed my PhD in 2018 at the University of Edinburgh in the CALVIN group supervised by Vittorio Ferrari (see here for my thesis). I spent three years as a postdoc in the Computer Vision and Machine Learning Group of Christoph Lampert at ISTA, the Institute of Science and Technology Austria. Since January 2022, I hold the post of Lecturer in Machine Learning, in the School of Computing Science at the University of Glasgow. My 'official' (not-so-interesting) homepage is here.

My curriculum vitae is available here.