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Datasets:
huanngzh
/
Objaverse-Rand6View

Tasks:
Text-to-3D
Image-to-3D
Text-to-Image
Modalities:
3D
Languages:
English
ArXiv:
Tags:
objaverse
3d
high-quality
License:
Dataset card Data Studio Files Community
Objaverse-Rand6View
File size: 3,522 Bytes 
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---
license: mit
task_categories:
- text-to-3d
- image-to-3d
- text-to-image
- image-to-image
language:
- en
tags:
- objaverse
- 3d
- high-quality
---

# Objaverse-Rand6View

[Github](https://github.com/huanngzh/MV-Adapter) | [Project Page](https://huanngzh.github.io/MV-Adapter-Page/) | [Paper](https://arxiv.org/abs/2412.03632)

## 1. Dataset Introduction

**TL;DR:** This dataset contains multi-view images that are rendered from a high-quality subset of [Objaverse](https://objaverse.allenai.org/), used in [MV-Adapter](https://huanngzh.github.io/MV-Adapter-Page/).
Features:
* Orthographic or perspective views (random)
* 1024x1024 resolution
* RGB, Depth, Normal, Camera

## 2. Data Extraction

```bash
sudo apt-get install git-lfs
git lfs install
git clone https://huggingface.co/datasets/huanngzh/Objaverse-Rand6View
cat Objaverse-Rand6View.part* > Objaverse-Rand6View.tar.gz
tar -xzvf Objaverse-Rand6View.tar.gz
```

## 3. File Structure

```bash
Objaverse-Rand6View
├── data
│   ├── 00
│   │   ├── 00a4d2b0c4c240289ed456e87d8b9e02
│   │   │   ├── color_0000.webp # rgb
│   │   │   ├── color_0001.webp
│   │   │   ├── ...
│   │   │   ├── color_0005.webp
│   │   │   ├── depth_0000.exr # depth
│   │   │   ├── depth_0001.exr
│   │   │   ├── ...
│   │   │   ├── depth_0005.exr
│   │   │   ├── normal_0000.webp # normal
│   │   │   ├── normal_0001.webp
│   │   │   ├── ...
│   │   │   ├── normal_0005.webp
│   │   │   └── meta.json # camera
│   │   ...
│   │   └── 00a6e74d8eeb428bb3e01b9361d8d57e
│   ├── 0a
│   ├── ...
│   └── zS
├── objaverse_list_6w.json # id list
└── objaverse_short_captions.json # captions
```

| 0000 | 0001 | 0002 | 0003 | 0004 | 0005 |
| - | - | - | - | - | - |
| ![image/webp](https://cdn-uploads.huggingface.co/production/uploads/6375d136dee28348a9c63cbf/m41t8mZsSo6o21_xf5Z3c.webp) | ![image/webp](https://cdn-uploads.huggingface.co/production/uploads/6375d136dee28348a9c63cbf/jBuFq_ZoA9uwj2r9RxrRV.webp) | ![image/webp](https://cdn-uploads.huggingface.co/production/uploads/6375d136dee28348a9c63cbf/JcYsNSpfX0AruiKXZ1Bhh.webp) | ![image/webp](https://cdn-uploads.huggingface.co/production/uploads/6375d136dee28348a9c63cbf/D8Zq6A2ZPVd-jDAsQdev1.webp) | ![image/webp](https://cdn-uploads.huggingface.co/production/uploads/6375d136dee28348a9c63cbf/1t_A5E4e6m6bH8i0ez95r.webp) | ![image/webp](https://cdn-uploads.huggingface.co/production/uploads/6375d136dee28348a9c63cbf/7JhJcM1ASKqPsDwwSMnlW.webp) |


## Citation

If you find this dataset useful, please cite:

```bash
@article{huang2024mvadapter,
  title={Mv-adapter: Multi-view consistent image generation made easy},
  author={Huang, Zehuan and Guo, Yuan-Chen and Wang, Haoran and Yi, Ran and Ma, Lizhuang and Cao, Yan-Pei and Sheng, Lu},
  journal={arXiv preprint arXiv:2412.03632},
  year={2024}
}

@inproceedings{deitke2023objaverse,
  title={Objaverse: A universe of annotated 3d objects},
  author={Deitke, Matt and Schwenk, Dustin and Salvador, Jordi and Weihs, Luca and Michel, Oscar and VanderBilt, Eli and Schmidt, Ludwig and Ehsani, Kiana and Kembhavi, Aniruddha and Farhadi, Ali},
  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
  pages={13142--13153},
  year={2023}
}
```

## Contact

[[email protected]](mailto:[email protected])