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Uada3d: Unsupervised adversarial domain adaptation for 3d object detection with sparse lidar and large domain gaps
In this study, we address a gap in existing unsupervised domain adaptation approaches on
LiDAR-based 3D object detection, which have predominantly concentrated on adapting …
LiDAR-based 3D object detection, which have predominantly concentrated on adapting …
Self-supervised learning with ensemble representations
K Han, M Lee - Engineering Applications of Artificial Intelligence, 2025 - Elsevier
Many computer vision applications, such as medical image processing, have struggled with
a lack of labeled data. Recently, contrastive self-supervised learning has made remarkable …
a lack of labeled data. Recently, contrastive self-supervised learning has made remarkable …