In recent years, point cloud representation has become one of the research hotspots in the
field of computer vision, and has been widely used in many fields, such as autonomous …

The robustness of 3D perception systems under natural corruptions from environments and
sensors is pivotal for safety-critical applications. Existing large-scale 3D perception datasets …

Abstract 3D object detection is an important task in autonomous driving to perceive the
surroundings. Despite the excellent performance, the existing 3D detectors lack the …

Majority of research in learning based methods has been towards designing and training
networks for specific tasks. However, many of the learning based tasks, across modalities …

This paper presents ShapeLLM, the first 3D Multimodal Large Language Model (LLM)
designed for embodied interaction, exploring a universal 3D object understanding with 3D …

We introduce a set of image transformations that can be used as corruptions to evaluate the
robustness of models as well as data augmentation mechanisms for training neural …

Abstract 3D object detection is an essential perception task in autonomous driving to
understand the environments. The Bird's-Eye-View (BEV) representations have significantly …

In recent years, 3D point clouds (PCs) have gained significant attention due to their diverse
applications across various fields, such as computer vision (CV), condition monitoring (CM) …

As 3D point cloud analysis has received increasing attention, the insufficient scale of point
cloud datasets and the weak generalization ability of networks become prominent. In this …