Computer Vision

Computer vision is one the core research fields of the Visual Computing section at DTU Compute.

Our highlights include

  • Visual data restoration
  • Statistical image modeling
  • Compression
  • Visual recognition with minimal supervision
  • Multimodal learning
  • Camera calibration
  • 3D scanning
  • Visual data restoration

    Many problems in computer vision involve conditional image generation, acquisition and display.. Deep learning has greatly advanced the quality of the generated images in recent years; however challenges still remain. These problems often come with paired training data, making the image generation supervised. We develop innovative image restoration techniques using deep neural networks. These techniques can solve many problems such as image denoising, demosaicing, super-resolution, and inpainting. We also work on video frame interpolation which is able to increase the temporal resolution of a video.

    For further information see:


    Dimitrios Papadopoulos
    Associate Professor
    DTU Compute
    Siavash Arjomand Bigdeli
    Associate Professor
    DTU Compute
    Morten Rieger Hannemose
    Assistant Professor
    DTU Compute

    Visual recognition with minimal supervision

    A fundamental component of most visual recognition systems is the learning procedure. Like humans, the machine needs to be trained beforehand with a lot of training examples to be able to learn visual models and make predictions in unseen data. Obtaining such data typically requires human annotation which is tedious, very expensive and time consuming. To alleviate this problem, we focus on developing efficient techniques for learning visual models with minimal supervision for the tasks of object detection and image segmentation. We have proposed weakly supervised models with efficient human interaction, human-in-the-loop schemes and label propagation techniques for efficient image annotation.

    For further information see:

    Camera calibration

    Having an accurately calibrated camera setup (intrinsics and extrinsics) is essential for many computer vision problems such as 3D scanning. We develop practical methods for highly accurate camera calibration

    For further information see:

    3D scanning

    Our lab has extensive experience in structured light 3D scanning. Recent improvements in projector technology, increased processing power, and new method developments with central contributions from our research group, it is now possible to perform faster and highly accurate structured light scans. This offers new opportunities for studying dynamic scenes, quality control, human-computer interaction and more.


    Computer vision is a central topic in the following DTU courses

    External references

    We also collaborate and are a part of the DTU 3D Imaging Center - 3DIM, which is our X-ray µCT laboratory.