Update README.md

README.md

@@ -3,15 +3,103 @@ license: odc-by
 language:
 - en
 viewer: false
+tags:
+- huggingscience
+- science
+- computer-vision
+- 3d
+- robotics
+- embodied-ai
+- graphics
+datasets:
+- allenai/objaverse
 ---
 
 # Objaverse
 
-Objaverse is a Massive Dataset with 800K+ Annotated 3D Objects.
+[![arXiv](https://img.shields.io/badge/arXiv-2212.08051-b31b1b.svg)](https://arxiv.org/abs/2212.08051)
+[![Website](https://img.shields.io/badge/🌐-Website-blue)](https://objaverse.allenai.org/)
+[![Hugging Face](https://img.shields.io/badge/🤗-Datasets-yellow)](https://huggingface.co/datasets/allenai/objaverse-xl)
+[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/15XpZMjrHXuky0IgBbXcsUtb_0g-XWYmN?usp=sharing)
+[![GitHub](https://img.shields.io/badge/GitHub-Repo-green)](https://github.com/allenai/objaverse-xl)
 
-More documentation is coming soon. In the meantime, please see our [paper](https://arxiv.org/abs/2212.08051) and [website](https://objaverse.allenai.org/) for additional details.
+## Overview
 
-# License
+Welcome to Objaverse, the world's largest 3D object dataset. With over 800,000 high-quality annotated 3D objects, this groundbreaking collection is designed to advance research in 3D vision, robotics, and artificial intelligence.
+
+<img src="https://objaverse.allenai.org/objaverse-xl/objaverse-xl.jpg" alt="Objaverse Dataset Overview" width="600"/>
+
+## Dataset Scale
+
+<img src="https://objaverse.allenai.org/objaverse-xl/scale-comparison.jpg" alt="Scale Comparison" width="600"/>
+
+Setting a new standard in 3D data resources, Objaverse is 100x larger than all other 3D datasets combined, enabling unprecedented opportunities for research and development in 3D understanding and generation.
+
+## Dataset Description
+
+### Dataset Summary
+
+Objaverse is a large-scale dataset of 3D models aimed at filling a critical gap in AI research by providing diverse, high-fidelity 3D data. The dataset includes:
+
+- 800,000+ 3D models
+- Descriptive captions and tags for each object
+- Animations for dynamic objects
+- Multiple object categories with rich intra-category diversity
+- High-quality renderings and metadata
+
+### Supported Tasks
+
+The dataset supports various research applications including:
+
+1. Training generative 3D models
+2. Improving tail category segmentation (LVIS benchmark)
+3. Training open-vocabulary object-navigation models for Embodied AI
+4. Creating benchmarks for robustness analysis of vision models
+5. Supporting research in computer graphics and 3D vision
+
+### Dataset Size and Format
+
+- Total Objects: 800,000+
+- Format: GLB/GLTF files
+- Additional Metadata: JSON files with annotations and licenses
+
+### Data Collection and Curation
+
+The dataset has been curated to ensure:
+
+- High-quality 3D models
+- Diverse object categories
+- Rich metadata and annotations
+- Proper licensing and attribution
+
+## Dataset Usage and Getting Started
+
+### Quick Start Resources
+
+- 📝 [Paper](https://arxiv.org/abs/2212.08051) - Technical details and methodology
+- 🌐 [Website](https://objaverse.allenai.org/) - Interactive demos and visualizations
+- 🤗 [Hugging Face Dataset](https://huggingface.co/datasets/allenai/objaverse-xl) - Download and use the dataset
+- 📓 [Google Colab Tutorial](https://colab.research.google.com/drive/15XpZMjrHXuky0IgBbXcsUtb_0g-XWYmN?usp=sharing) - Interactive tutorial to get started
+- 💻 [GitHub Repository](https://github.com/allenai/objaverse-xl) - Code and scripts
+
+### Integration Examples
+
+<img src="https://objaverse.allenai.org/objaverse-xl/blender.jpg" alt="Blender Compatibility" width="500"/>
+
+Each Objaverse object can be rendered and imported into Blender. See the [rendering scripts](https://github.com/allenai/objaverse-xl/tree/main/scripts/rendering) to get started.
+
+### Model Applications
+
+<img src="https://objaverse.allenai.org/objaverse-xl/zero123-xl.jpg" alt="Zero123-XL Examples" width="500"/>
+
+The dataset has enabled training of powerful 3D foundation models like Zero123-XL, demonstrating impressive 3D generation capabilities. Key applications include:
+
+- 🎨 **3D Generation**: Train and use generative models for 3D content creation
+- 🔄 **Single Image to 3D**: Convert single images to 3D models using Zero123-XL
+- 🤖 **Robotics**: Train embodied AI agents for object interaction and navigation
+- 🖼️ **Computer Vision**: Improve object detection and segmentation tasks
+
+## License
 
 The use of the dataset as a whole is licensed under the [ODC-By v1.0](https://opendatacommons.org/licenses/by/1-0/) license. Individual objects in Objaverse are all licensed as creative commons distributable objects, and may be under the following licenses:
 
@@ -23,7 +111,7 @@ The use of the dataset as a whole is licensed under the [ODC-By v1.0](https://op
 
 The metadata will provide the license for each object.
 
-# Citation
+## Citation
 
 To cite Objaverse, please use the following BibTeX entry:
 
@@ -36,4 +124,4 @@ To cite Objaverse, please use the following BibTeX entry:
   journal={arXiv preprint arXiv:2212.08051},
   year={2022}
 }
-```
+```