no code implementations • 16 Apr 2024 • Sinisa Stekovic, Stefan Ainetter, Mattia D'Urso, Friedrich Fraundorfer, Vincent Lepetit
In our experiments, we apply our algorithm to reconstruct 3D objects in the ScanNet dataset and evaluate our results against CAD model retrieval-based reconstructions.
2 code implementations • 12 Sep 2023 • Stefan Ainetter, Sinisa Stekovic, Friedrich Fraundorfer, Vincent Lepetit
We present an automated and efficient approach for retrieving high-quality CAD models of objects and their poses in a scene captured by a moving RGB-D camera.
2 code implementations • 22 Dec 2022 • Stefan Ainetter, Sinisa Stekovic, Friedrich Fraundorfer, Vincent Lepetit
We present an automatic method for annotating images of indoor scenes with the CAD models of the objects by relying on RGB-D scans.
no code implementations • 22 Nov 2021 • Stefan Ainetter, Christoph Böhm, Rohit Dhakate, Stephan Weiss, Friedrich Fraundorfer
In this paper, we present a novel deep neural network architecture for joint class-agnostic object segmentation and grasp detection for robotic picking tasks using a parallel-plate gripper.
1 code implementation • 12 Jul 2021 • Stefan Ainetter, Friedrich Fraundorfer
In this work, we introduce a novel, end-to-end trainable CNN-based architecture to deliver high quality results for grasp detection suitable for a parallel-plate gripper, and semantic segmentation.
Ranked #1 on Robotic Grasping on Cornell Grasp Dataset