3 accepted papers
Monocular self-supervised depth estimation can be easily applied in many areas since only a single camera is required. However, current methods do not predict well in depth borders. Besides, factors such as occlusion and texture sparsity can lead to the failure of the photometric consistency, affect…
Visual odometry (VO) is an essence of vision-based localization and mapping system where existing learning-based approaches utilize CNN and RNN to model camera motion and gain promising results. However, these methods lack full use of the relationship between spatial characteristics and temporal clu…
Recently, unsupervised methods for monocular visual odometry (VO), with no need for quantities of expensive labeled ground truth, have attracted much attention. However, these methods are inadequate for long-term odometry task, due to the inherent limitation of only using monocular visual data and t…