Researcher

Martin Danelljan

Martin Danelljan is a computer vision researcher whose work on visual object tracking and 3D vision runs from Linköping University through ETH Zurich to Apple. With Michael Felsberg, Fahad Khan and Gustav Häger, he won the 2014 Visual Object Tracking Challenge, defended his Linköping doctoral thesis in 2018, and received the Best Nordic Thesis Prize at SCIA 2019. He coauthored the ATOM and discriminative model prediction trackers in 2019 and the RePaint diffusion inpainting method in 2022, and at ETH Zurich he was a postdoc and then a research group leader. Since November 2023, he is a senior computer vision research engineer in Apple's 3D Vision group, where he builds a team working on 3D computer vision at a global scale.

Now at
Apple

Timeline

  1. 2014

    Winning the VOT Challenge

    A prize-winning degree project in object tracking leads him to doctoral studies at Linköping University. In 2014, he wins the Visual Object Tracking Challenge with Michael Felsberg, Fahad Khan and Gustav Häger, and also the OpenCV State-of-the-Art Vision Challenge.

  2. 2016

    Best paper at ICPR

    He receives the best paper award at ICPR 2016 and achieves a top rank in the VOT2016 challenge.

  3. 2018

    Doctorate and Singulareye

    In June 2018, he defends his thesis, Learning Convolution Operators for Visual Tracking, as the first doctoral thesis associated with the WASP research programme, after working at Linköping's Computer Vision Laboratory. In 2018, he also founds the company Singulareye with two other doctoral students.

  4. 2019

    The ATOM and DiMP trackers

    In 2019, he is first author of ATOM, a CVPR 2019 tracker that predicts the overlap between a target and its bounding box and gains 15% over the previous best approach on TrackingNet at over 30 FPS. He also coauthors Learning Discriminative Model Prediction for Tracking with Goutam Bhat, Luc Van Gool and Radu Timofte, an end-to-end tracker that sets a new state of the art on 6 benchmarks.

  5. 2019

    Two awards in 2019

    His doctoral thesis wins the Best Nordic Thesis Prize at SCIA 2019. He also receives the best student paper award at BMVC 2019 for Tracking the Known and the Unknown by Leveraging Semantic Information, written with Ardhendu Shekhar Tripathi, Luc Van Gool and Radu Timofte.

  6. 2019–2023

    Group leader at ETH Zurich

    From 2019 to 2021, he is a postdoc at ETH Zurich in Radu Timofte's team, with Luc Van Gool as co-supervisor, and his research covers online and meta-learning for visual tracking and video object segmentation and deep probabilistic models for image generation. He goes on to lead a research group at ETH Zurich and founds Elevate3D.

  7. 2022

    The RePaint inpainting method

    In 2022, he coauthors RePaint with Andreas Lugmayr, Andres Romero, Fisher Yu, Radu Timofte and Luc Van Gool. The method is a denoising diffusion probabilistic model approach to inpainting that applies to even extreme masks.

  8. Since November 2023

    Research engineer at Apple

    He joins Apple in November 2023 as a senior computer vision research engineer in the 3D Vision group. There he builds a team working on 3D computer vision at a global scale.

Career

  1. Since 2023AppleSenior Computer Vision Research Engineer
  2. 2019–2023ETH ZurichPostdoc, Research Group Leader
  3. Until 2018Linköping University
  4. From 2018SingulareyeCo-founder
  5. Elevate3DFounder

Education

  1. Linköping UniversityPhD

Sources and credits

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  1. Highly cited LiU articles on computer vision - Linköping University liu.se. Checked 21 October 2026.
  2. From a degree project to 9000 citations and a company | ELLIIT elliit.se. Checked 21 October 2026.
  3. Visual tracking: from correlation filters to end-to-end discriminative model prediction cmp.felk.cvut.cz. Checked 21 October 2026.
  4. Martin Danelljan defends first WASP associated doctoral thesis | WASP wasp-sweden.org. Checked 21 October 2026.
  5. LiU a leader within AI - Linköping University liu.se. Checked 21 October 2026.
  6. [1811.07628] ATOM: Accurate Tracking by Overlap Maximization arxiv.org. Checked 21 October 2026.
  7. [1904.07220] Learning Discriminative Model Prediction for Tracking arxiv.org. Checked 21 October 2026.
  8. Radu Timofte, Computer Vision Lab, University of Wurzburg cvlai.net. Checked 21 October 2026.
  9. Martin Danelljan martin-danelljan.github.io. Checked 21 October 2026.
  10. [2201.09865] RePaint: Inpainting using Denoising Diffusion Probabilistic Models arxiv.org. Checked 21 October 2026.