XD-MAP generates pseudo labels for LiDAR semantic segmentation from camera images using parametric maps, improving 2D and 3D segmentation performance by up to 32.3 mIoU without manual labeling.
V oxel transformer for 3d object detection
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A semi-supervised 3D object detection framework with a learnable module for adaptive pseudo-label selection via score fusion, context-aware thresholds, and soft supervision.
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XD-MAP: Cross-Modal Domain Adaptation via Semantic Parametric Maps for Scalable Training Data Generation
XD-MAP generates pseudo labels for LiDAR semantic segmentation from camera images using parametric maps, improving 2D and 3D segmentation performance by up to 32.3 mIoU without manual labeling.
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Learning Adaptive Pseudo-Label Selection for Semi-Supervised 3D Object Detection
A semi-supervised 3D object detection framework with a learnable module for adaptive pseudo-label selection via score fusion, context-aware thresholds, and soft supervision.