Assistant Professor in Visual Computing at Durham University. Stuart's research focus is on Visual Reasoning to understand the layout of visual content from Iconography (e.g. Sketches) to 3D Scene understanding and their implications on methods of interaction. He is currently a co-I on the RePAIR EU FET, DCitizens EU Twinning, and BoSS EU Lighthouse. He was a co-I on the MEMEX RIA EU H2020 project coordinated at IIT for increasing social inclusion with Cultural Heritage. Stuart has previously held a Researcher & PostDoc positions at IIT as well as PostDocs at University College London (UCL), and the University of Surrey. Also, at the University of Surrey, Stuart was awarded his PhD on visual information retrieval for sketches. Stuart holds an External Scientist at IIT, Honorary roles UCL and UCL Digital Humanities, and an international collaborator of ITI/LARSyS. He also regularly organises Vision for Art (VISART) workshop and Humanities-orientated tutorials and was Program Chair at British Machine Conference (BMVC) 2021.

Stuart James

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Research interests

My research activities fit broadly into Spatial Reasoning — how we can reason about the layout of objects in space in both 2D and 3D to provide insight or retrieve relevant information. My research has a keen interest on varied data types including those from the Humanities such as Art and Cultural Heritage.


Exploring using Depth and Knowledge to answer questions specifically related to the layout of a 3D scene from a 2D perspective.

Visual Question & Answering

Detection, Representation and Reasoning on simplified representations or symbols such as Sketch, Line, Hatching, Motifs or icons.

Abstract & Iconography Reasoning

Identifying and retrieving relevant knowledge held within Knowledge Graphs to support Computer Vision tasks such as Visual Question and Answering or reasoning on location.

Knowledge Retrieval & Reasoning

Reconstructing the semantic relational structure of the scene using geometry and knowledge. Providing advanced interaction for questioning and reasoning.

Scene Graph

Principally on layout of content in 2D or 3D and how to make decisions that influence about a path or option linked with Visual Question and Answering

Planning & Reasoning

We have explored using sketches to search collections of videos using Visual Storyboarding to express the sequence of events in the target clip.

Sketch based Retrieval

We are using sequences to retrieve information providing a broader context than a one-off search. We have demonstrated through Free-Hand storyboarding and storey synthesis.

Visual Narratives and Stories

Within VR we explored the use free-hand sketching in an Immersive Environment (VR) with multiple modalities for the task of retrieval.

Interaction in Virtual Reality

Providing storytelling experiences overlaying information of surrounding Cultural Heritage and the stories of the particpants in the MEMEX Project.

Interaction in Augmented Reality

Cultural Heritage & Digital Humanities

Assistive Technologies

Robotics

Research Group & Collaborators

Research Topic: Optimising camera localisation in urban scenes

Collaborator with Dr Alessio Del Bue (IIT)

Dr Matteo Toso

PostDoc Collaborator

Research Topic: RePAIR Fresco 3D reconstruction and assembly

Collaborator with Dr Alessio Del Bue (IIT)

Dr Theodore Tsesmelis

PostDoc Collaborator

Allumni

Davide Talon

PhD Student

Mohamed Dahy Abdelaher Elkhouly

PhD Student

Dr Matteo Taiana

PostDoc Collaborator

Àlex Solé Gómez

Research Fellow

Dr Daniele Giunchi

External Collaborator

Openings

Looking to do a PhD?

Our group is always looking for good PhD candidates, so if you are interested in doing a PhD in Vision-based Spatial Reasoning please contact me to discuss the options. For more details review research areas and publications especially before making an inquiry or application.

Current Funding options:

    • Doctoral Training Partnerships (DTPs):
      • Funded by UK Research Councils (e.g., EPSRC, BBSRC, NERC).
      • Provide tuition fees, a stipend, and research training support.
    • Industry-funded PhDs:
      • Collaborative projects with companies.
      • Often part of Knowledge Transfer Partnerships
    • International Scholarships:
    • Self-funding:
      • Students cover their own tuition and living costs.
      • May combine with part-time work (visa permitting) or personal savings.

Outline available at: FindAPhD

More details on what can you expect

How to apply!

Reach out with your CV and a brief statement of your research interests and why you are interested in doing a PhD with us and how you plan to fund your PhD. If there is a mutual interest we will have a brief conversation and detail the application process at Durham University. You will then submit an application then we will arrange an interview with myself and the potential second supervisor. You will then recieve on the outcome of your application typically within a couple of weeks of the interview.

Contact to discuss a PhD

Call for Expression of Interest in MSCA Postdoctoral Fellowships

Open call for interest in co-writing a MSCA Postdoctoral Fellowship on Computer Vision at Durham University. Wide array of topics we can discuss, but includes everything from digitisation to understanding and reasoning. The MSCA is an international collaborative program so a long-term secondment is required.

Project Duration: 1-2 Years

The EU provides support for the recruited researcher in the form of

  • A living allowance
  • A mobility allowance
  • If applicable, family, long-term leave and special needs allowances

In addition, funding is provided for

  • research, training and networking activities
  • management and indirect costs

Full details at

https://marie-sklodowska-curie-actions.ec.europa.eu/actions/postdoctoral-fellowships

Eligibility:

  • PhD or 4 years of full-time research experience
  • Mobility Rule: The researcher must not have resided or carried out their main activity (work, studies, etc.) in the country of the host organization (i.e. UK) for more than 12 months in the 36 months immediately before the call deadline.
  • Experience Level: The researcher must have a maximum of 8 years of research experience after obtaining their PhD. This excludes career breaks (e.g., parental leave) and time spent outside research.

Dates:

  • Call opens: 8 May 2025
  • EOI Deadline: 1 July 2025
  • Call Deadline: 10 September 2025

How to apply!

Please send me an Expression of Interest (EOI) with "MSCA Postdoctoral Fellowships" in the subject line. Your EOI should include the following:

  • A concise 1-page outline of your proposed project, highlighting your innovative ideas and how they align with the fellowship's goals.
  • Your latest CV, showcasing your academic achievements, research experience, and any relevant skills or publications.

I am looking for the brightest and most motivated researchers to join this exciting program. This is your chance to work on transformative projects, gain international experience, and contribute to groundbreaking advancements in Computer Vision. I look forward to reviewing your application and exploring the potential for collaboration!

How to contact me

Latest Blog Post

18 Jul 2023 . research . New position at Durham University Comments

Durham University

As of 1st September 2023, I will be taking up a position as Assistant Professor in Visual Computing at Durham University working in the VIViD group. This marks a major transition for me, as I move from being a contract-based Assistant Professor (or Researcher RTDa in the Italian system) to a permanent member of staff (i.e. Lecturer).

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Previous posts

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Latest Publication

2025 Maps from Motion (MfM): Generating 2D Semantic Maps from Sparse Multi-view Images

World-wide detailed 2D maps require enormous collective efforts. OpenStreetMap is the result of 11 million registered users manually annotating the GPS location of over 1.75 billion entries, including distinctive landmarks and common urban objects. At the same time, manual annotations can include errors and are slow to update, limiting the map's accuracy. Maps from Motion (MfM) is a step forward to automatize such time-consuming map making procedure by computing 2D maps of semantic objects directly from a collection of uncalibrated multi-view images. From each image, we extract a set of object detections, and estimate their spatial arrangement in a top-down local map centered in the reference frame of the camera that captured the image. Aligning these local maps is not a trivial problem, since they provide incomplete, noisy fragments of the scene, and matching detections across them is unreliable because of the presence of repeated pattern and the limited appearance variability of urban objects. We address this with a novel graph-based framework, that encodes the spatial and semantic distribution of the objects detected in each image, and learns how to combine them to predict the objects' poses in a global reference system, while taking into account all possible detection matches and preserving the topology observed in each image. Despite the complexity of the problem, our best model achieves global 2D registration with an average accuracy within 4 meters (i.e., below GPS accuracy) even on sparse sequences with strong viewpoint change, on which COLMAP has an 80% failure rate. We provide extensive evaluation on synthetic and real-world data, showing how the method obtains a solution even in scenarios where standard optimization techniques fail.

Accepted at International Conference on 3D Vision (3DV'25) in Singapore.

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Contact

To find out more about our research you can find me at...

Department of Computer Science

Durham University
Room MS2099, Mathematical Sciences and Computer Science Building, Durham University, Upper Mountjoy, Stockton Road, DURHAM, DH1 3LE