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djiajunustc avatar

djiajunustc/3D-LLaVA

0
View on GitHub↗
98 stars·8 forks·Python·7 views

3D LLaVA

3D-LLaVA: Towards Generalist 3D LMMs with Omni Superpoint Transformer

Features

  • 3D Scene Understanding - Generalist 3D large multimodal model using omni superpoint transformers.

Star history

Star history chart for djiajunustc/3d-llavaStar history chart for djiajunustc/3d-llava

How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.

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Frequently asked questions

What does djiajunustc/3d-llava do?

3D-LLaVA: Towards Generalist 3D LMMs with Omni Superpoint Transformer

What are the main features of djiajunustc/3d-llava?

The main features of djiajunustc/3d-llava are: 3D Scene Understanding.

What are some open-source alternatives to djiajunustc/3d-llava?

Open-source alternatives to djiajunustc/3d-llava include: anjiecheng/spatialrgpt — arxiv / Huggingface. baaivision/uni3d — Uni3D: Exploring Unified 3D Representation at Scale. chat-3d/chat-3d — This is a repo for paper "Chat-3D: Data-efficiently Tuning Large Language Model for Universal Dialogue of 3D Scenes".… embodied-generalist/embodied-generalist — An Embodied Generalist Agent in 3D World. hanxunyu/inst3d-lmm — Inst3D-LMM: Instance-Aware 3D Scene Understanding with Multi-modal Instruction Tuning. 3d-rft/3d-rft — ``bibtex @inproceedings{linghu20263d, title={3D-RFT: Reinforcement Fine-Tuning for Video-based 3D Scene…

Open-source alternatives to 3D LLaVA

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  • chat-3d/chat-3dChat-3D avatar

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    This is a repo for paper "Chat-3D: Data-efficiently Tuning Large Language Model for Universal Dialogue of 3D Scenes". paper, project page

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  • 3d-rft/3d-rft3D-RFT avatar

    3D-RFT/3D-RFT

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    `bibtex @inproceedings{linghu20263d, title={3D-RFT: Reinforcement Fine-Tuning for Video-based 3D Scene Understanding}, author={Linghu, Xiongkun and Huang, Jiangyong and Jia, Baoxiong and Huang, Siyuan}, booktitle={International Conference on Machine Learning}, year={2026} } `

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