Bin Cheng

most cited

S^{3}

Net: Semantic-Aware Self-supervised Depth Estimation with Monocular Videos and Synthetic Data

1 citations · 1 across the 1 of their papers we have counts for

collaborators

2 papers

cs.IT2021

Wiener Filter versus Recurrent Neural Network-based 2D-Channel Estimation for V2X Communications

Moritz Benedikt Fischer, Sebastian Dörner, Sebastian Cammerer +4

We compare the potential of neural network (NN)-based channel estimation with classical linear minimum mean square error (LMMSE)-based estimators, also known as Wiener filtering. F…

cs.CV2020★ 1 cited

$S^{3}$ Net: Semantic-Aware Self-supervised Depth Estimation with Monocular Videos and Synthetic Data

Bin Cheng, Inderjot Singh Saggu, Raunak Shah +2

Solving depth estimation with monocular cameras enables the possibility of widespread use of cameras as low-cost depth estimation sensors in applications such as autonomous driving…

Wiener Filter versus Recurrent Neural Network-based 2D-Channel Estimation for V2X Communications

S3Net: Semantic-Aware Self-supervised Depth Estimation with Monocular Videos and Synthetic Data

$S^{3}$ Net: Semantic-Aware Self-supervised Depth Estimation with Monocular Videos and Synthetic Data