Dense captioning in 3D point clouds is an emerging vision-and-language task involving
object-level 3D scene understanding. Apart from coarse semantic class prediction and …

Abstract 3D dense captioning aims to generate multiple captions localized with their
associated object regions. Existing methods follow a sophisticated" detect-then-describe" …

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 …

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 …

3D dense captioning stands as a cornerstone in achieving a comprehensive understanding
of 3D scenes through natural language. It has recently witnessed remarkable achievements …

3D dense captioning requires a model to translate its understanding of an input 3D scene
into several captions associated with different object regions. Existing methods adopt a …

3D dense captioning aims to semantically describe each object detected in a 3D scene,
which plays a significant role in 3D scene understanding. Previous works lack a complete …

Abstract 3D dense captioning is a recently-proposed novel task, where point clouds contain
more geometric information than the 2D counterpart. However, it is also more challenging …

The unprecedented advancements in Large Language Models (LLMs) have created a
profound impact on natural language processing but are yet to fully embrace the realm of 3D …

Observing that the 3D captioning task and the 3D grounding task contain both shared and
complementary information in nature, in this work, we propose a unified framework to jointly …