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ViPR: Visual-Odometry-aided Pose Regression for 6DoF Camera Localization
[article]
2019
arXiv
pre-print
Visual Odometry (VO) accumulates a positional drift in long-term robot navigation tasks. Although Convolutional Neural Networks (CNNs) improve VO in various aspects, VO still suffers from moving obstacles, discontinuous observation of features, and poor textures or visual information. While recent approaches estimate a 6DoF pose either directly from (a series of) images or by merging depth maps with the optical flow (OF), research that combines absolute pose regression with OF is limited. We
arXiv:1912.08263v2
fatcat:soynuvfnwbgkxcnihwiw5rcz5u