In this paper, we propose an end-to-end online 3D video object detector that operates on point cloud sequences.
The quality of machine translation has increased remarkably over the past years, to the degree that it was found to be indistinguishable from professional human translation in a number of empirical investigations.
To address the second challenge, we propose an Attention-based Multi-level Integrator Module to give the model the ability to assign different weights to multi-level feature maps.
This paper considers multi-agent reinforcement learning (MARL) in networked system control.
Learning to reconstruct 3D shapes using 2D images is an active research topic, with benefits of not requiring expensive 3D data.
In this context, we investigated a method based on U-Net to detect the document edges and text regions in ID images.