Harald Schafer

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Harald Schafer trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Anastasios I. Mourikis
  2. Mingyang Li
  3. Ethan Rublee
  4. Francois Caron
  5. Stergios I. Roumeliotis
  6. Ben M. Chen
  7. Vincent Rabaud
  8. Emmanuel Duflos
  9. Jianbo Shi

Papers from Harald Schafer's perspective

Ordered by how strongly the researchers Harald Schafer trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Good features to track
  2. A Multi-State Constraint Kalman Filter for Vision-aided Inertial Navigation (Proceedings 2007 IEEE International Conference on Robotics and Automation)
  3. ORB: An efficient alternative to SIFT or SURF
  4. High-precision, consistent EKF-based visual-inertial odometry (Int. J. Robotics Res.)
  5. Unmanned Rotorcraft Systems
  6. GPS/IMU data fusion using multisensor Kalman filtering: introduction of contextual aspects (Information Fusion)
  7. Distinctive Image Features from Scale-Invariant Keypoints
  8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  9. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  10. ImageNet classification with deep convolutional neural networks

Their papers