While multi-party conversations are often less structured than monologues and documents,
they are implicitly organized by semantic level correlations across the interactive turns, and …

3D dense captioning, as an emerging vision-language task, aims to identify and locate each
object from a set of point clouds and generate a distinctive natural language sentence for …

3D visual grounding is a critical skill for household robots, enabling them to navigate,
manipulate objects, and answer questions based on their environment. While existing …

Autonomous driving systems generally employ separate models for different tasks resulting
in intricate designs. For the first time, we leverage singular multimodal large language …

This paper describes a domestic service robot (DSR) that fetches everyday objects and
carries them to specified destinations according to free-form natural language instructions …

Training machines to understand natural language and interact with humans is one of the
major goals of artificial intelligence. Recent years have witnessed an evolution from …

In the context of autonomous driving environment perception, multi-modal fusion plays a
pivotal role in enhancing robustness, completeness, and accuracy, thereby extending the …

Radar is ubiquitous in autonomous driving systems due to its low cost and good adaptability
to bad weather. Nevertheless, the radar detection performance is usually inferior because its …

Rapid advancements in 3D vision-language (3D-VL) tasks have opened up new avenues
for human interaction with embodied agents or robots using natural language. Despite this …

We introduce the task of dense captioning in 3D scans from commodity RGB-D sensors. As
input, we assume a point cloud of a 3D scene; the expected output is the bounding boxes …