Recent research has evidenced the significant potentials of Large Language Models (LLMs)
in handling challenging tasks within 3D scenes. However, current models are constrained to …

3D scene understanding has gained significant attention due to its wide range of
applications. However, existing methods for 3D scene understanding are limited to specific …

Referring Expression Comprehension (REC) is a fundamental task in the vision and
language domain, which aims to locate an image region according to a natural language …

Contrastive learning has emerged as a promising paradigm for 3D open-world
understanding ie aligning point cloud representation to image and text embedding space …

We introduce the task of localizing a flexible number of objects in real-world 3D scenes
using natural language descriptions. Existing 3D visual grounding tasks focus on localizing …

In this work we study the problem of using referential language to identify common objects in
real-world 3D scenes. We focus on a challenging setup where the referred object belongs to …

Abstract 3D dense captioning aims to describe individual objects by natural language in 3D
scenes, where 3D scenes are usually represented as RGB-D scans or point clouds …

Localization and perception research for Autonomous Driving is mainly focused on camera
and LiDAR data, rarely on radar data. We apply an automated labeling pipeline to …

We introduce a new task of question generation to eliminate the uncertainty of referring
expressions in 3D indoor environments (3D-REQ). Referring to an object using natural …

Robust perception is a vital component for ensuring safe autonomous and assisted driving.
Automotive radar (77 to 81 GHz), which offers weather-resilient sensing, provides a …