9 citations · 9 across the 2 of their papers we have counts for
5 papers · 1 filter
PIZZA: A Powerful Image-only Zero-Shot Zero-CAD Approach to 6 DoF Tracking
Van Nguyen Nguyen, Yuming Du, Yang Xiao +2
Estimating the relative pose of a new object without prior knowledge is a hard problem, while it is an ability very much needed in robotics and Augmented Reality. We present a meth…
Single Image Depth Prediction with Wavelet Decomposition
Michaël Ramamonjisoa, Michael Firman, Jamie Watson +2
We present a novel method for predicting accurate depths from monocular images with high efficiency. This optimal efficiency is achieved by exploiting wavelet decomposition, which…
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…
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…
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…