license: other
license_name: nvidia-non-commercial-license
license_link: https://huggingface.co/nvidia/PartPacker/blob/main/LICENSE
language:
- en
PartPacker
Description:
In this work, we propose a new end-to-end framework for part-level 3D object generation. Given a single input image, our method generates high-quality 3D shapes with an arbitrary number of complete and semantically meaningful parts. Most existing methods generate a single mesh with all parts fused together, which limits the ability to edit or manipulate individual parts. A key challenge in part-level generation is that different objects may have a varying number of components. To address this problem, we introduce a dual volume packing strategy that organizes all parts into two complementary volumes, allowing for the creation of complete and interleaved parts that assemble into the final object. Experiments show that our model achieves better quality, diversity, and generalization than previous image-based part-level generation methods.
This model is ready for non-commercial use.
License/Terms of Use:
Model Architecture:
Architecture Type: Transformer
Input:
Input Type(s): Image Input Format(s): RGB Image Input Parameters: 2D Image Other Properties Related to Input: Condition for the model.
Output:
Output Type(s): Mesh Output Format: GLB Output Parameters: 3D Mesh Other Properties Related to Output: Generated 3D shape with parts.
Supported Hardware Microarchitecture Compatibility
- NVIDIA Ampere
- NVIDIA Hopper
Supported Operating System(s)
- Linux
Model Version(s):
v1.0
Training Dataset:
Objaverse-XL Properties: We use about 250k mesh data, which is a subset from the Objaverse-XL with part-level annotations. Dataset License(s): The use of the dataset as a whole is licensed under the ODC-By v1.0 license.
Inference:
Pytorch
Ethical Considerations:
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