Update README.md

README.md

@@ -59,10 +59,9 @@ configs:
 
 ## Overview
 
-BlockGen-3D is a large-scale dataset of voxelized 3D models with accompanying text descriptions, specifically designed for text-to-3D generation tasks. By processing and voxelizing models from the [Objaverse dataset](https://huggingface.co/datasets/allenai/objaverse), we have created a standardized representation that is particularly suitable for training 3D generative models.
-
-Our dataset provides two types of representations: shape-only models represented as binary occupancy grids, and colored models with full RGBA information. Each model is represented in a 32×32×32 voxel grid, striking a balance between detail preservation and computational efficiency. This uniform representation makes the dataset especially suitable for training diffusion models and other deep learning architectures for 3D generation.
+BlockGen-3D is a large-scale dataset of voxelized 3D models with accompanying text descriptions, specifically designed for text-to-3D generation tasks. By processing and voxelizing models from the [Objaverse dataset](https://huggingface.co/datasets/allenai/objaverse), we have created a standardized representation that is particularly suitable for training 3D diffusion models.
 
+Our dataset provides two types of representations: shape-only models represented as binary occupancy grids, and colored models with full RGBA information. Each model is represented in a 32×32×32 voxel grid. 
 The dataset contains 542,292 total samples, with:
 - 515,177 training samples
 - 27,115 test samples
@@ -160,7 +159,9 @@ dataloader = DataLoader(
 
 ## Visualization Examples
 
-
+![Dataset Usage Example](https://huggingface.co/datasets/PeterAM4/blockgen-3d/resolve/main/comparison_wooden.gif)
+![Dataset Usage Example](https://huggingface.co/datasets/PeterAM4/blockgen-3d/resolve/main/comparison_char.gif)
+*Dataset Usage Example - Showing voxelization process*
 
 ## Dataset Creation Process
 
@@ -184,21 +185,25 @@ Our dataset was created through the following steps:
 
 If you use this dataset in your research, please cite:
 
+```
 @misc{blockgen2024,
   title={BlockGen-3D: A Large-Scale Dataset for Text-to-3D Voxel Generation},
   author={Peter A. Massih},
   year={2024},
   publisher={Hugging Face}
 }
+```
 
 Please also cite the original Objaverse dataset:
 
+```
 @article{objaverse2023,
   title={Objaverse: A Universe of Annotated 3D Objects},
   author={Matt Deitke and Dustin Schwenk and Jordi Salvador and Luca Weihs and Oscar Michel and Eli VanderBilt and Ludwig Schmidt and Kiana Ehsani and Aniruddha Kembhavi and Ali Farhadi},
   journal={arXiv preprint arXiv:2304.02643},
   year={2023}
 }
+```
 
 ## Limitations