59 citations · 109 across the 34 of their papers we have counts for
4 papers · 2 filters
ROI-10D: Monocular Lifting of 2D Detection to 6D Pose and Metric Shape
Fabian Manhardt, Wadim Kehl, Adrien Gaidon
We present a deep learning method for end-to-end monocular 3D object detection and metric shape retrieval. We propose a novel loss formulation by lifting 2D detection, orientation,…
Explaining the Ambiguity of Object Detection and 6D Pose From Visual Data
Fabian Manhardt, Diego Martin Arroyo, Christian Rupprecht +4
3D object detection and pose estimation from a single image are two inherently ambiguous problems. Oftentimes, objects appear similar from different viewpoints due to shape symmetr…
Deep Model-Based 6D Pose Refinement in RGB
Fabian Manhardt, Wadim Kehl, Nassir Navab +1
We present a novel approach for model-based 6D pose refinement in color data. Building on the established idea of contour-based pose tracking, we teach a deep neural network to pre…
BOP: Benchmark for 6D Object Pose Estimation
Tomas Hodan, Frank Michel, Eric Brachmann +13
We propose a benchmark for 6D pose estimation of a rigid object from a single RGB-D input image. The training data consists of a texture-mapped 3D object model or images of the obj…