3 papers
cs.CV2020
Predicting Sharp and Accurate Occlusion Boundaries in Monocular Depth Estimation Using Displacement Fields
Michael Ramamonjisoa, Yuming Du, Vincent Lepetit
Current methods for depth map prediction from monocular images tend to predict smooth, poorly localized contours for the occlusion boundaries in the input image. This is unfortunat…
cs.CV2019
On Object Symmetries and 6D Pose Estimation from Images
Giorgia Pitteri, Michaël Ramamonjisoa, Slobodan Ilic +1
Objects with symmetries are common in our daily life and in industrial contexts, but are often ignored in the recent literature on 6D pose estimation from images. In this paper, we…
cs.CV2019
SharpNet: Fast and Accurate Recovery of Occluding Contours in Monocular Depth Estimation
Michaël Ramamonjisoa, Vincent Lepetit
We introduce SharpNet, a method that predicts an accurate depth map for an input color image, with a particular attention to the reconstruction of occluding contours: Occluding con…