The acquisition of inductive bias through pointlevel contrastive learning holds paramount
significance in point cloud pre-training. However, the square growth in computational …

Multi-modal 3D object detection has received growing attention as the information from
different sensors like LiDAR and cameras are complementary. Most fusion methods for 3D …

Fashion design usually requires multiple designers to discuss and collaborate to complete a
set of fashion designs, and the efficiency of the sketching process is another challenge for …

Whereas contrastive learning eliminates the need for labeled data, existing methods may
suffer from inadequate features due to the conventional single shared encoder structure and …

We propose a co-part segmentation method that takes a set of point clouds of the same
category as input where neither a ground truth label nor a prior network is required. With …

In recent years, 3D vision has gained increasing prominence in practical applications such
as autonomous driving and robotics. However, the scarcity of large labeled point cloud …

In this paper, we present a novel Cross-architecture Relational Consistency (CRC)
framework for point cloud self-supervised learning. Since the features produced by encoders …