Computer Graphics and Image Processing

Computer generated image of a living room

The computer graphics and image processing group is driving a number of research projects directed towards the development of theory and methodology for image capture, image analysis and image synthesis.  

A common theme within our projects is to develop algorithms and techniques for measuring and digitizing real environments, lighting conditions and material properties so that this information can be used to simulate the interaction between light and matter in a scene to create photo-realistic computer graphics images.

With a strong foundation in theoretically oriented research, the group is active within a number of demonstrator projects and industrial and academic collaborations directed towards development of state-of-the-art applications within the focus areas. We are currently working with projects directed towards:

  • New algorithms and methodologies for photo realistic image synthesis based on Monte Carlo integration
  • High Dynamic Range (HDR) imaging and video capture and statistical image reconstruction
  • Tone mapping and compression of HDR images and video
  • Capture, processing and Light field imaging
  • Appearance capture and modelling of material properties for photo-realistic image synthesis
  • Algorithms and methodology for capture and reconstruction of lighting, geometry and material properties of real scenes based on sensor data

News

Latest publications

2026

Emelie Fälton, Isabelle Strömstedt, Mathis Brossier, Andreas C. Göransson, Konrad Schönborn, Amy Loutfi, Erik Sundén, Mujtaba Fadhil Jawad, Suleiman Yadgar, Johanna Björklund, Mario Romero, Anders Ynnerman, Lonni Besançon (2026) Children's Expectations, Engagement, and Evaluation of an LLM-enabled Spherical Visualization Platform in the Classroom EuroVis 2026 Education Papers (Conference paper)
Konstantina Vouzouneraki, Erik Ylipää, Tommy Olsson, Katarina Berinder, Charlotte Hoybye, Maria Petersson, Sophie Bensing, Anna-Karin Akerman, Henrik Borg, Bertil Ekman, Jonas Robért, Britt Eden Engstrom, Oskar Ragnarsson, Pia Burman, Per Dahlqvist (2026) Detection of Acromegaly From Facial Images Using Machine Learning: A Comparison With Clinical Experts Journal of the Endocrine Society, Vol. 10, Article bvaf203 (Article in journal) Continue to DOI
Maria Eidenskog, Wiktoria Glad, Saghi Hajisharif, Fatemeh Johari, Katerina Vrotsou (2026) Just, Adaptive and Meaningful (JAM): Energy Use Predictions for the Built Environment through Synthetic Data Proceedings of the 59th Hawaii International Conference on System Sciences, p. 5541-5548 (Conference paper)

2025

Taridzo Chomutare, Aleksandar Barbic, Laura-Maria Peltonen, Silja Elunurm, Peter Lundberg, Arne Jönsson, Emma Eneling, Ciprian-Virgil Gerstenberger, Troels Siggaard, Raivo Kolde, Oskar Jerdhaf, Martin Hansson, Alexandra Makhlysheva, Miroslav Muzny, Erik Ylipää, Søren Brunak, Hercules Dalianis (2025) Implementing a Nordic-Baltic Federated Health Data Network: A Case Report MEDINFO 2025 — Healthcare Smart × Medicine Deep: Proceedings of the 20th World Congress on Medical and Health Informatics, p. 1241-1245 (Conference paper) Continue to DOI
Behnaz Kavoosighafi, Rafal Mantiuk, Saghi Hajisharif, Ehsan Miandji, Jonas Unger (2025) A Neural Quality Metric for BRDF Models
Yifan Ding (2025) AIM 2025 challenge on inverse tone mapping report: Methods and results Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops (Conference paper)
Behnaz Kavoosighafi, Saghi Hajisharif, Jonas Unger, Ehsan Miandji (2025) Adaptive Sampling for BRDF Acquisition Computer graphics forum (Print), Article e70289 (Article in journal) Continue to DOI
Behnaz Kavoosighafi, Rafał K. Mantiuk, Saghi Hajisharif, Ehsan Miandji, Jonas Unger (2025) A Neural Quality Metric for BRDF Models Journal of Physics, Conference Series, Vol. 3128, p. 012015-012015 (Article in journal) Continue to DOI
Yifan Ding, Arturas Aleksandrauskas, Amirhossein Ahmadian, Jonas Unger, Fredrik Lindsten, Gabriel Eilertsen (2025) Revisiting Likelihood-Based Out-of-Distribution Detection by Modeling Representations IMAGE ANALYSIS, SCIA 2025, PT II, p. 166-179 (Conference paper) Continue to DOI
Nithesh Chandher Karthikeyan, Jonas Unger, Gabriel Eilertsen (2025) Towards Controllable Image Generation through Representation-Conditioned Diffusion Models Towards Controllable Image Generation through Representation-Conditioned Diffusion Models (Conference paper)

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