LiDAR-UDA: Self-ensembling Through Time for Unsupervised LiDAR Domain Adaptation

Unsupervised Domain Adaptation for LiDAR Panoptic SegmentationПодробнее

[RA-L 2022 Summary Vid] Lidar-Agnostic 3D Detection for Unsupervised Multi-Target Domain AdaptationПодробнее

ICML AI- Domain Adaptation for Time Series, Feature/Label Shifts(4/15)Подробнее

[CVPRW] Rethinking Ensemble-Distillation for Unsupervised Domain AdaptationПодробнее

[RAL/IROS 2022 Slides] Lidar-Agnostic 3D Detection for Unsupervised Multi-Target Domain AdaptationПодробнее

MS3D++: Ensemble of Experts for Multi-Source Unsupervised Domain Adaptation in 3D Object DetectionПодробнее

Self-Distillation for Unsupervised 3D Domain AdaptationПодробнее

Part 21: unsupervised intr-domain adaptation for semantic segmentation through self-supervisionПодробнее

SqueezeSegV2Подробнее

Part 71: Multi-source domain adaptation with collaborative learning for semantic segmentationПодробнее

Part 58: divide and contrast: source-free domain adaptation via adaptive contrastive learningПодробнее

Part 23: discriminator-free unsupervised domain adaptation for multi-label image classificationПодробнее

CVPR 2021 Regressive Domain Adaptation for Unsupervised Keypoint DetectionПодробнее

Unsupervised Intra-Domain Adaptation for Semantic Segmentation Through Self-SupervisionПодробнее

Talk: Supervised & Unsupervised Approaches for LiDAR Perception in Urban Environments by C StachnissПодробнее

Stanford Seminar - Self-Supervised Pseudo-Lidar NetworksПодробнее

PR-468: Maximum Classifier Discrepancy for Unsupervised Domain AdaptationПодробнее

xMUDA: Cross-Modal Unsupervised Domain Adaptation for 3D Semantic SegmentationПодробнее

Domain Adaptation in LiDAR Semantic Segmentation by Aligning Class Distributions: SupplementaryПодробнее