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NVIDIA
NVIDIA
ESS DNN Stereo Disparity
Model
NVIDIA
NVIDIA
ESS DNN Stereo Disparity

ESS is a DNN that estimates disparity for a stereo image pair and returns a continuous disparity map for the given left image.

This model is backed by NVIDIA's Plus Plus (++) Promise
to learn more about the quality of the datasets used to train this model.
FieldResponse
Generatable or Reverse engineerable personally-identifiable information?Neither.
Was consent obtained for any PII used?Yes.
Protected classes used to create this model?Age, Gender, Race, Skin Colors.
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 collected for the development of the model, was it collected by NVIDIA?Yes.
If PII collected for the development of the model by NVIDIA, do you maintain or have access to disclosures made to data subjects?Yes.
If PII 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 the 3D assets used to generate the data. Real data contains the date and time of the recording and a operator entered text description of the recording at start.
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 Policyhttps://www.nvidia.com/en-us/about-nvidia/privacy-policy

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