diff --git a/README.md b/README.md
index a49850b..3cf5891 100644
--- a/README.md
+++ b/README.md
@@ -1 +1,36 @@
-# Awesome-LVLM-Attack
\ No newline at end of file
+# Awesome-LVLM-Attack [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)
+A **continual** collection of papers related to Text-guided 3D Visual Grounding (T-3DVG).
+
+Text-guided 3D visual grounding (T-3DVG) 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.
+T-3DVG 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 the T-3DVG community, we've summarized existing T-3DVG methods in our survey paper👍.
+
+
+> If you find some important work missed, it would be super helpful to let me know (`dzliu@stu.pku.edu.cn`). Thanks!
+
+> If you find our survey useful for your research, please consider citing:
+
+```
+@article{liu2024survey,
+  title={A Survey on Text-guided 3D Visual Grounding: Elements, Recent Advances, and Future Directions},
+  author={Liu, Daizong and Liu, Yang and Huang, Wencan and Hu, Wei},
+  journal={arXiv preprint arXiv},
+  year={2024}
+}
+```
+
+**Table of Contents**
+- [Fully-supervised two-stage approach](#Fully-Supervised-Two-Stage)
+- [Fully-supervised one-stage approach](#Fully-Supervised-One-Stage)
+- [Weakly-supervised approach](#Weakly-supervised)
+- [Approaches using No Point Cloud Input](#Other-Modality)
+- [Approaches using LLMs](#LLMs-based)
+---
+
+## Fully-Supervised-Two-Stage
+* **ScanRefer: 3D Object Localization in RGB-D Scans using Natural Language** | [Github](https://github.com/daveredrum/ScanRefer)
+  * Dave Zhenyu Chen, Angel X. Chang, Matthias Nießner
+  * Technical University of Munich, Simon Fraser University
+  * [ECCV2020] https://arxiv.org/abs/1912.08830
+  * A dataset, two-stage approach, proposal-then-selection