Search Results for author:
Found 8 papers, 2 papers with code
H-SLAM: Hybrid Direct-Indirect Visual SLAM
The recent success of hybrid methods in monocular odometry has led to many attempts to generalize the performance gains to hybrid monocular SLAM.
OSPC: Online Sequential Photometric Calibration
Photometric calibration is essential to many computer vision applications.
The benefits of synthetic data for action categorization
In this paper, we study the value of using synthetically produced videos as training data for neural networks used for action categorization.
Change your singer: a transfer learning generative adversarial framework for song to song conversion
Transfer learning improves the GV by 35% and the MS by 13% on average.
A Unified Formulation for Visual Odometry
Monocular Odometry systems can be broadly categorized as being either Direct, Indirect, or a hybrid of both.
FDMO: Feature Assisted Direct Monocular Odometry
Visual Odometry (VO) can be categorized as being either direct or feature based.
Keyframe-based monocular SLAM: design, survey, and future directions
Extensive research in the field of monocular SLAM for the past fifteen years has yielded workable systems that found their way into various applications in robotics and augmented reality.
Identifying Good Training Data for Self-Supervised Free Space Estimation
This paper proposes a novel technique to extract training data from free space in a scene using a stereo camera.
