Add metadata and improve dataset card

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  1. README.md +29 -4
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- ## ScanNet Data Preparation
 
 
 
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- This repository contains the ScanNet dataset split into two main compressed archives: 3D scene data and 2D frame data.
 
 
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- More detalis can refer to the GitHub: https://github.com/WHB139426/TAB-Agent [![](https://img.shields.io/badge/Github-181717?style=flat&logo=github&logoColor=white)](https://github.com/WHB139426/TAB-Agent)
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- </div>
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  ### 1. Unzip the Data
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  Before using the data, please download and extract the zip files. You can use the following commands in your terminal:
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  │ └── ...
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  ├── scene0000_01/
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  └── ...
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ```
 
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+ ---
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+ task_categories:
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+ - zero-shot-object-detection
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+ ---
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+ # Think, Act, Build: An Agentic Framework with Vision Language Models for Zero-Shot 3D Visual Grounding
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+
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+ This repository contains the ScanNet dataset (3D scene data and 2D frame data) and refined annotations used for the paper [Think, Act, Build: An Agentic Framework with Vision Language Models for Zero-Shot 3D Visual Grounding](https://huggingface.co/papers/2604.00528).
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+ TAB is a dynamic agentic framework designed for zero-shot 3D Visual Grounding (3D-VG). By operating directly on raw RGB-D streams, TAB reformulates 3D grounding from a static proposal matching task into an active semantic reasoning and geometric reconstruction process.
 
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+ - **GitHub:** [https://github.com/WHB139426/TAB-Agent](https://github.com/WHB139426/TAB-Agent)
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+ - **Paper:** [https://huggingface.co/papers/2604.00528](https://huggingface.co/papers/2604.00528)
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+
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+ ## ScanNet Data Preparation
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+ This repository contains the ScanNet dataset split into two main compressed archives: 3D scene data and 2D frame data.
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  ### 1. Unzip the Data
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  Before using the data, please download and extract the zip files. You can use the following commands in your terminal:
 
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  │ └── ...
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  ├── scene0000_01/
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  └── ...
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+ ```
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+
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+ ## Citation
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+
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+ If you find this work useful, please consider citing:
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+
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+ ```bibtex
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+ @misc{wang2026thinkactbuildagentic,
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+ title={Think, Act, Build: An Agentic Framework with Vision Language Models for Zero-Shot 3D Visual Grounding},
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+ author={Haibo Wang and Zihao Lin and Zhiyang Xu and Lifu Huang},
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+ year={2026},
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+ eprint={2604.00528},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CV},
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+ url={https://arxiv.org/abs/2604.00528},
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+ }
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  ```