Text-guided 3D visual grounding (T-3DVG), which aims to locate a specific object that semantically corresponds to a language query from a complicated 3D scene, has drawn increasing attention in the 3D research community over the past few years. Compared to 2D visual grounding, this task presents great potential and challenges due to its closer proximity to the real world and the complexity of data collection and 3D point cloud source processing. In this survey, we attempt to provide a comprehensive overview of the T-3DVG progress, including its fundamental elements, recent research advances, and future research directions. To the best of our knowledge, this is the first systematic survey on the T-3DVG task. Specifically, we first provide a general structure of the T-3DVG pipeline with detailed components in a tutorial style, presenting a complete background overview. Then, we summarize the existing T-3DVG approaches into different categories and analyze their strengths and weaknesses. We also present the benchmark datasets and evaluation metrics to assess their performances. Finally, we discuss the potential limitations of existing T-3DVG and share some insights on several promising research directions. The latest papers are continually collected at https://github.com/liudaizong/Awesome-3D-Visual-Grounding.

文本引导的三维视觉定位（T-3DVG）是从复杂的三维场景中定位与语言查询在语义上对应的对象，近年来已经在三维研究领域引起了越来越多的关注。本综述试图全面概述T-3DVG的进展，包括基本要素、最新研究进展和未来研究方向，并提供了详细的教程式的管道结构、现有方法的分类和性能评估指标，以及现有方法的潜在限制和未来研究方向。

文本引导的3D视觉定位调查：要素、最新进展与未来方向