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Understanding the Challenges When 3D Semantic Segmentation Faces Class Imbalanced and OOD Data
(3) The trust scores are unreliable for classes whose features are confused with other classes.
Are We Hungry for 3D LiDAR Data for Semantic Segmentation? A Survey and Experimental Study
Finally, a systematic survey to the existing efforts to solve the data hunger problem is conducted on both methodological and dataset's viewpoints, followed by an insightful discussion of remaining problems and open questions To the best of our knowledge, this is the first work to analyze the data hunger problem for 3D semantic segmentation using deep learning techniques that are addressed in the literature review, statistical analysis, and cross-dataset and cross-algorithm experiments.
Off-Road Drivable Area Extraction Using 3D LiDAR Data
We propose a method for off-road drivable area extraction using 3D LiDAR data with the goal of autonomous driving application.
SemanticPOSS: A Point Cloud Dataset with Large Quantity of Dynamic Instances
3D semantic segmentation is one of the key tasks for autonomous driving system.
