Publications in the project Learnable Camera Motion Models

Publications are sorted acording to type and listed in reverse chronological order. Click on the name of the publication to view the abstract and a link to the full paper.

Conference Papers

• Density Adaptive Point Set Registration
  Felix Järemo Lawin, Martin Danelljan, Fahad Khan, Per-Erik Forssén, Michael Felsberg
  CVPR18, June 2018
  
• Spline Error Weighting for Robust Visual-Inertial Fusion
  Hannes Ovrén, Per-Erik Forssén
  CVPR18, June 2018
  
• Attentional Masking for Pre-trained Deep Networks
  Marcus Wallenberg, Per-Erik Forssén
  IROS17, September 2017
  
• What is the best depth-map compression for Depth Image Based Rendering?
  Jens Ogniewski, Per-Erik Forssén
  CAIP17, August 2017
  
• BriefMatch: Dense binary feature matching for real-time optical flow estimation
  Gabriel Eilertsen, Per-Erik Forssén, Jonas Unger
  SCIA17, June 2017
  
• Pushing the Limits for View Prediction in Video Coding
  Jens Ogniewski, Per-Erik Forssén
  VISAPP17, February-March 2017
  
• Efficient Multi-Frequency Phase Unwrapping using Kernel Density Estimation
  Felix Järemo Lawin, Per-Erik Forssén, Hannes Ovrén
  ECCV16, October 2016
  
• Ground Truth for Rolling Shutter Visual-Inertial SLAM and Camera-IMU Calibration
  Hannes Ovrén, Per-Erik Forssén
  SSBA16, March 2016
  
• Gyroscope-based Video Stabilisation With Auto-Calibration
  Hannes Ovrén, Per-Erik Forssén
  ICRA15, May 2015
  
• Active Gaze Stabilization
  Martin Lesmana, Axel Landgren, Per-Erik Forssén, Dinesh K. Pai
  ICVGIP14, December 2014
  

Theses Journals and Book Chapters

• Trajectory Representation and Landmark Projection for Continuous-Time Structure from Motion
  Hannes Ovrén, Per-Erik Forssén
  International Journal of Robotics Research, May 2019
  
• Depth Data Processing and 3D Reconstruction Using the Kinect v2
  Master's Thesis, LiTH-ISY-EX--15/4884--SE
  September 2015
  
• Improving RGB-D Scene Reconstruction using Rolling Shutter Rectification
  H. Ovrén, P.-E. Forssén, D. Törnqvist
  Springer Verlag, January 2015
  

Project

More information can be found on the LCMM project page.