Dec 16, 2019 · We introduce ConvPoseCNN, a fully convolutional architecture that avoids cutting out individual objects. Instead we propose pixel-wise, dense prediction.

In this work, we introduce. ConvPoseCNN, a fully convolutional architecture that avoids cutting out individual objects. Instead we pro- pose pixel-wise, dense ...

In this work, we introduce. ConvPoseCNN, a fully convolutional architecture that avoids cutting out individual objects. Instead we pro- pose pixel-wise, dense ...

Dec 16, 2019 · This work introduces ConvPoseCNN, a fully convolutional architecture that avoids cutting out individual objects, and proposes pixel-wise, ...

Abstract—Estimating the 6D pose of known objects is impor- tant for robots to interact with the real world. The problem is challenging due to the variety of ...

Apr 11, 2020 · In this work, we introduce ConvPoseCNN, a fully convolutional architecture that avoids cutting out individual objects. Instead we propose pixel- ...

This repository summarizes papers and codes for 6D Object Pose Estimation of rigid objects, which means computing the 6D transformation from the object ...

Our ConvPoseCNN architecture for convolutional pose estimation. During ag- gregation, candidate quaternions are selected according to the semantic segmentation.

Nov 25, 2023 · This paper proposes a fully convolutional and parallel architecture that obtains the 3D translation and orientation for object poses from the same pixel-wise ...

Object pose estimation is a key perceptual capability in robotics. We propose a fully-convolutional extension of the PoseCNN method, which densely predicts ...