Despite impressive advancements in multimodal compositional reasoning approaches, they
are still limited in their flexibility and efficiency by processing fixed modality inputs while …

Segmentation of three-dimensional (3D) point clouds is fundamental in comprehending
unstructured structural and morphological data. It plays a critical role in research related to …

Nowadays, pre-training big models on large-scale datasets has achieved great success and
dominated many downstream tasks in natural language processing and 2D vision, while pre …

In this paper we create an RGB-D 3D object detector targeted at indoor robotics use cases
where one modality may be unavailable due to a specific sensor setup or a sensor failure …

Manual annotation of every point in a point cloud is a costly and labor-intensive process.
While weakly supervised point cloud semantic segmentation (WSPCSS) with sparse …

In this work, we survey recent studies on masked image modeling (MIM), an approach that
emerged as a powerful self-supervised learning technique in computer vision. The MIM task …

Autonomous driving technology faces significant safety challenges due to the lack of a
global perspective and the limitations of long-range perception capabilities. It is widely …