suwesh/RACECAR-lidar-to-bev-image-labeled
Converted lidar point clouds(3D) into RGB bird's eye view images(2D) of the Racecar Dataset's multi-slow-poli race scenario. With labels for object (other racecars on the track) detection and trajectory generation/planning. For more details visit: https://www.kaggle.com/datasets/suwesh/train-im-labeled. The images are segmented scenes along space-time dimensions with each segmentation covering a scene history of 15 frames. The neural network used to perform the segmentations is the Parallel… See the full description on the dataset page: https://huggingface.co/datasets/suwesh/RACECAR-lidar-to-bev-image-labeled.
Converted lidar point clouds(3D) into RGB bird's eye view images(2D) of the Racecar Dataset's multi-slow-poli race scenario. With labels for object (other racecars on the track) detection and trajectory generation/planning. For more details visit: https://www.kaggle.com/datasets/suwesh/train-im-labeled.
The images are segmented scenes along space-time dimensions with each segmentation covering a scene history of 15 frames.
The neural network used to perform the segmentations is the Parallel Perception Network ( https://huggingface.co/suwesh/Parallel-Perception-Network ) model's segmentation network.
Original Racecar Dataset paper link: https://arxiv.org/pdf/2306.03252.pdf