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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.
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For more details visit: https://www.kaggle.com/datasets/suwesh/train-im-labeled.
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Original Racecar Dataset paper link: https://arxiv.org/pdf/2306.03252.pdf
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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.
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For more details visit: https://www.kaggle.com/datasets/suwesh/train-im-labeled.
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The images are segmented scenes along space-time dimensions with each segmentation covering a scene history of 15 frames.
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The neural network used to perform the segmentations is the Parallel Perception Network ( https://huggingface.co/suwesh/Parallel-Perception-Network ) model's segmentation network.
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Original Racecar Dataset paper link: https://arxiv.org/pdf/2306.03252.pdf
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