Search Results for author:
Found 2 papers, 1 papers with code
PoET: Pose Estimation Transformer for Single-View, Multi-Object 6D Pose Estimation
It is a challenging task due to object symmetries, clutter and occlusion, but it becomes more challenging when additional information, such as depth and 3D models, is not provided.
Variational Inference to Measure Model Uncertainty in Deep Neural Networks
The variational density is designed in such a way that the a posteriori uncertainty of the network parameters is represented per network layer and depending on the estimated parameter expectation values.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
