BEV-Seg: Bird’s Eye View Semantic Segmentation Using Geometry and Semantic Point Cloud

June 2020

tl;dr: Detached model to perform domain adaptation sim2real.

Overall impression

Two stage model to bridge domain gap. This is very similar to GenLaneNet for 3D LLD prediction. The idea of using semantic segmentation to bridge the sim2real gap is explored in many BEV semantic segmentation tasks such as BEV-Seg, CAM2BEV, VPN.

The first stage model already extracted away domain-dependent features and thus the second stage model can be used as is.

The GT of BEV segmentation is difficult to collect in most domains. The simulated segmentation GT can be obtained in abundance with simulator such as CARLA.

Key ideas

Technical details