4 accepted papers
Estimating a scene reconstruction and the camera motion from in-body videos is challenging due to several factors, e.g. the deformation of in-body cavities or the lack of texture. In this paper we present Endo-Depth-and-Motion, a pipeline that estimates the 6-degrees-of-freedom camera pose and dense
The problem of 3D layout recovery in indoor scenes has been a core research topic for over a decade. However, there are still several major challenges that remain unsolved. Among the most relevant ones, a major part of the state-of-the-art methods make implicit or explicit assumptions on the scenes
The assumption of scene rigidity is typical in SLAM algorithms. Such a strong assumption limits the use of most visual SLAM systems in populated real-world environments, which are the target of several relevant applications like service robotics or autonomous vehicles. In this letter we present Dyna
Dense and accurate 3-D mapping from a monocular sequence is a key technology for several applications and still an open research area. This letter leverages recent results on single-view convolutional network (CNN)-based depth estimation and fuses them with multiview depth estimation. Both approache