EfficientLPS: Efficient LiDAR Panoptic Segmentation

• URL: http://arxiv.org/abs/2102.08009v1
• Date: Tue, 16 Feb 2021 08:14:52 GMT
• Title: EfficientLPS: Efficient LiDAR Panoptic Segmentation
• Authors: Kshitij Sirohi, Rohit Mohan, Daniel B\"uscher, Wolfram Burgard, Abhinav Valada
• Abstract summary: We present the novel Efficient LiDAR Panoptic architecture that addresses multiple challenges in segmenting LiDAR point clouds. EfficientLPS comprises of a novel shared backbone that encodes with strengthened geometric transformation modeling capacity. We benchmark our proposed model on two large-scale LiDAR datasets.
• Score: 30.249379810530165
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Panoptic segmentation of point clouds is a crucial task that enables autonomous vehicles to comprehend their vicinity using their highly accurate and reliable LiDAR sensors. Existing top-down approaches tackle this problem by either combining independent task-specific networks or translating methods from the image domain ignoring the intricacies of LiDAR data and thus often resulting in sub-optimal performance. In this paper, we present the novel top-down Efficient LiDAR Panoptic Segmentation (EfficientLPS) architecture that addresses multiple challenges in segmenting LiDAR point clouds including distance-dependent sparsity, severe occlusions, large scale-variations, and re-projection errors. EfficientLPS comprises of a novel shared backbone that encodes with strengthened geometric transformation modeling capacity and aggregates semantically rich range-aware multi-scale features. It incorporates new scale-invariant semantic and instance segmentation heads along with the panoptic fusion module which is supervised by our proposed panoptic periphery loss function. Additionally, we formulate a regularized pseudo labeling framework to further improve the performance of EfficientLPS by training on unlabelled data. We benchmark our proposed model on two large-scale LiDAR datasets: nuScenes, for which we also provide ground truth annotations, and SemanticKITTI. Notably, EfficientLPS sets the new state-of-the-art on both these datasets.

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