30 citations · 38 across the 5 of their papers we have counts for
5 papers
3D-LaneNet+: Anchor Free Lane Detection using a Semi-Local Representation
Netalee Efrat, Max Bluvstein, Shaul Oron +3
3D-LaneNet+ is a camera-based DNN method for anchor free 3D lane detection which is able to detect 3d lanes of any arbitrary topology such as splits, merges, as well as short and p…
Synthetic-to-Real Domain Adaptation for Lane Detection
Noa Garnett, Roy Uziel, Netalee Efrat +1
Accurate lane detection, a crucial enabler for autonomous driving, currently relies on obtaining a large and diverse labeled training dataset. In this work, we explore learning fro…
Semi-Local 3D Lane Detection and Uncertainty Estimation
Netalee Efrat, Max Bluvstein, Noa Garnett +3
We propose a novel camera-based DNN method for 3D lane detection with uncertainty estimation. Our method is based on a semi-local, BEV, tile representation that breaks down lanes i…
Performance Advantages of Deep Neural Networks for Angle of Arrival Estimation
Oded Bialer, Noa Garnett, Tom Tirer
The problem of estimating the number of sources and their angles of arrival from a single antenna array observation has been an active area of research in the signal processing com…
3D-LaneNet: End-to-End 3D Multiple Lane Detection
Noa Garnett, Rafi Cohen, Tomer Pe'er +2
We introduce a network that directly predicts the 3D layout of lanes in a road scene from a single image. This work marks a first attempt to address this task with on-board sensing…