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Model
FoundationPose is a unified foundation model for 6D object pose estimation and tracking of objects.
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| Field | Response |
|---|---|
| Generatable or Reverse engineerable personally-identifiable information? | Neither. |
| Was consent obtained for any PII used? | Does not apply since we do not have people objects in our dataset. |
| Protected classes used to create this model? | None. |
| How often is dataset reviewed? | Before Every Release. |
| Is a mechanism in place to honor data subject right of access or deletion of personal data? | Yes. |
| If PII was collected for the development of the model, was it collected by NVIDIA? | Yes. |
| If PII was collected for the development of the model by NVIDIA, do you maintain or have access to disclosures made to data subjects? | Yes. |
| If PII was collected for the development of this AI model, was it minimised to only what was required? | Yes. Dataset does not contain audio or GPS location data. |
| Is there provenance for all datasets used in training? | Synthetically generated data is completely traceable to the original 3D assets used to generate the data. Real data was only used to generate the synthetic data, and was not used in directly training the model. |
| Are we able to identify and trace source of dataset? | Yes. |
| Does data labeling (annotation, metadata) comply with privacy laws? | Yes. |
| Is data compliant with data subject requests for data correction or removal, if such a request was made? | Yes. |
| Applicable NVIDIA Privacy Policy | https://www.nvidia.com/en-us/about-nvidia/privacy-policy |