Adversarial scene adaptation for camera pose regression

A training method, comprising:

• by a first model:
• generating a first vector representation based on a first image from a first domain using first weight values;
• generating a second vector representation based on the first vector representation;
• and
• generating a first 6 degrees of freedom (DoF) pose of a first camera that captured the first image based on the second vector representation using second weight values;
• by a second model:
• generating a third vector representation based on a second image from a second domain using the first weight values,
• wherein the second domain is different than the first domain;
• generating a fourth vector representation based on the third vector representation;
• and
• generating a second 6 DoF pose of a second camera that captured the second image based on the fourth vector representation and using the second weight values;
• based on first and second outputs from the first and second models, generating a discriminator output indicative of whether the first and second images are from the same domain;
• and
• based on the discriminator output, selectively adjusting at least one of:
• at least one of the first weight values;
• and
• at least one of the second weight values.

A non-transitory computer readable medium comprising code that, when executed by one or more processors, performs a training method, comprising:

• by a first model:
• generating a first vector representation based on a first image from a first domain using first weight values;
• generating a second vector representation based on the first vector representation;
• and
• generating a first 6 degrees of freedom (DoF) pose of a first camera that captured the first image based on the second vector representation using second weight values;
• by a second model:
• generating a third vector representation based on a second image from a second domain using the first weight values,
• wherein the second domain is different than the first domain;
• generating a fourth vector representation based on the third vector representation;
• and
• generating a second 6 DoF pose of a second camera that captured the second image based on the fourth vector representation and using the second weight values;
• based on first and second outputs from the first and second models, generating a discriminator output indicative of whether the first and second images are from the same domain;
• and
• based on the discriminator output, selectively adjusting at least one of:
• at least one of the first weight values;
• and
• at least one of the second weight values.

A training system, comprising:

• a first means for:
• generating a first vector representation based on a first image from a first domain using first weight values;
• generating a second vector representation based on the first vector representation;
• and
• generating a first 6 degrees of freedom (DoF) pose of a first camera that captured the first image based on the second vector representation using second weight values;
• a second means for:
• generating a third vector representation based on a second image from a second domain using the first weight values,
• wherein the second domain is different than the first domain;
• generating a fourth vector representation based on the third vector representation;
• and
• generating a second 6 DoF pose of a second camera that captured the second image based on the fourth vector representation and using the second weight values;
• a third means for, based on first and second outputs from the first and second means, generating a discriminator output indicative of whether the first and second images are from the same domain;
• and
• a fourth means for, based on the discriminator output, selectively adjust at least one of:
• at least one of the first weight values;
• and
• at least one of the second weight values.

A pose estimation training system, comprising:

• a first model configured to generate a first 6 degrees of freedom (DoF) pose of a first camera that captured a first image from a first domain;
• a second model configured to generate a second 6 DoF pose of a second camera that captured a second image from a second domain, where the second domain is different than the first domain;
• a discriminator module configured to, based on first and second outputs from the first and second encoder modules, generate a discriminator output indicative of whether the first and second images are from the same domain;
• and
• a training control module configured to, based on the discriminator output, selectively adjust at least one weight value shared by the first model and the second model.