3D segmentation is a fundamental and challenging problem in computer vision with
applications in autonomous driving and robotics. It has received significant attention from the …

In recent years, transformer-based models have exhibited considerable potential in point
cloud instance segmentation. Despite the promising performance achieved by existing …

Abstract 3D segmentation is a fundamental and challenging problem in computer vision with
applications in autonomous driving and robotics. It has received significant attention from the …

The proliferation of 2D foundation models has sparked research into adapting them for open-
world 3D instance segmentation. Recent methods introduce a paradigm that leverages …

Recent approaches have successfully focused on the segmentation of static reconstructions,
thereby equipping downstream applications with semantic 3D understanding. However, the …

Transformer-based methods have become the dominant approach for 3D instance
segmentation. These methods predict instance masks via instance queries, ranking them by …

The performance of 3D object detection in large outdoor point clouds deteriorates
significantly in an unseen environment due to the inter-domain gap. To address these …

Recent 3D Instance Segmentation methods typically follow a similar paradigm; they encode
hundreds of instance-wise candidates with instance-specific information in various ways and …