SAM-Net: Semantic probabilistic and attention mechanisms of dynamic objects for self-supervised depth and camera pose estimation in visual odometry applications
Work
Year: 2021
Type: article
Source: Pattern Recognition Letters
Cites: 47
Cited by: 13
Related to: 10
FWCI: 1.72
Citation percentile (by year/subfield): 64.41
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Sustainable Development Goal No poverty
Open Access status: green