Papers › Point-Bind & Point-LLM: Aligning Point Cloud with Multi-modality for 3D Understanding,...
Point-Bind & Point-LLM: Aligning Point Cloud with Multi-modality for 3D Understanding, Generation, and Instruction Following
Ziyu Guo, Renrui Zhang, Xiangyang Zhu, Yiwen Tang, Xianzheng Ma, Jiaming Han, Kexin Chen, Peng Gao, Xianzhi Li, Hongsheng Li, Pheng-Ann Heng
We introduce Point-Bind, a 3D multi-modality model aligning point clouds with 2D image, language, audio, and video. Guided by ImageBind, we construct a joint embedding space between 3D and multi-modalities, enabling many promising applications, e.g., any-to-3D generation, 3D embedding arithmetic, and 3D open-world understanding. On top of this, we further present Point-LLM, the first 3D large language model (LLM) following 3D multi-modal instructions. By parameter-efficient fine-tuning techniques, Point-LLM injects the semantics of Point-Bind into pre-trained LLMs, e.g., LLaMA, which requires no 3D instruction data, but exhibits superior 3D and multi-modal question-answering capacity. We hope our work may cast a light on the community for extending 3D point clouds to multi-modality applications. Code is available at https://github.com/ZiyuGuo99/Point-Bind_Point-LLM.
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Code
Syntology Ran 13 of 20 code samples harvested from 3 repositories linked to this paper; 7 have no recorded run. Of those that ran: 2 ran · honoured contract; 1 ran · violated contract; 1 ran · our draft was wrong; 3 ran · fixture could not drive it; 6 ran with no contract checked.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| 3D Question Answering (3D-QA) | 3D MM-Vet | Point-Bind & Point-LLM | Overall Accuracy | 23.5 | #5 of 5 | Archive leaderboard | report |
| Generative 3D Object Classification | ModelNet40 | Point-Bind LLM | ModelNet40 (Average) | 45.81 | #6 of 6 | Archive leaderboard | report |
| Generative 3D Object Classification | Objaverse | Point-Bind LLM | Objaverse (Average) | 5.25 | #7 of 7 | Archive leaderboard | report |
| Generative 3D Object Classification | Objaverse | Point-Bind LLM | Objaverse (C) | 4.50 | #7 of 7 | Archive leaderboard | report |
| Generative 3D Object Classification | Objaverse | Point-Bind LLM | Objaverse (I) | 6.00 | #7 of 7 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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