Open badai-nguyen opened 7 months ago
This pull request has been automatically marked as stale because it has not had recent activity.
@StepTurtle please check this work too, link it when creating a new issue.
Note: 2D multiple header YOLOX was trained and is going to update by https://github.com/autowarefoundation/autoware/pull/4012
Checklist
Description
As I described https://github.com/orgs/autowarefoundation/discussions/3974, we (TIER IV) and other teams are also facing difficult to deal with unknown from plants, raindrops/smoke/splash pointcloud or pointcloud of ground segmentation fail.
Current pointcloud filters including dual_return_filter, outlier_filter, ground_segmentation only based on points kinematics information. Compare_map_filter compare pointcloud with map to remove un-movable objects but it frequently fail with growing plants, tree.. etc.
It should be helpful if image semantic information could be used and fused with pointcloud to remove unnecessary pointclouds for autonomous driving such as pointcloud of plants in background, or drivable area.
Purpose
To deploy some kind of image semantic or instance segmentation model and matching with pointcloud to filter pointcloud.
Possible approaches
Publish some 2d mask image of segmentation information or kind of less important image region information for filtering
Create new node to fuse image pixel level with pointcloud and remove pointcloud in less important image region.
Definition of done