Abstract: The embodiments are directed to generating synthetic data. For example, in some examples, a method for creating 2D images of an object with annotation points is carried out by a processing unit. The method includes considering a synthetic 3D model of the object, named synthetic object, with annotation points correctly placed on the synthetic object. The method also includes generating several synthetic objects with different poses and different brightness conditions. Further, the method includes considering several 2D images with different backgrounds and different brightness conditions. For each 2D image, the method includes insertion of a generated synthetic object in the 2D image.

Abstract: Certain aspects of the present disclosure provide techniques for generating three-dimensionally coherent training data for image-detection machine learning models. Embodiments include receiving a first image of an object from a first perspective and a second image of the object from a second perspective. Embodiments include receiving user input identifying a location in the first image corresponding to a point on the object. Embodiments include displaying a range of possible locations in the second image corresponding to the point on the object based on the location in the first image. Embodiments include generating training data for a machine learning model based on updated user input associated with the range of possible locations.

Abstract: Certain aspects of the present disclosure provide techniques for determining a pose of a three-dimensional deformable object. Embodiments include providing one or more inputs to a machine learning model based on a computer-generated three-dimensional deformable object that has a known pose. Embodiments include determining, based on one or more outputs from the machine learning model in response to the one or more inputs, a two-dimensional signature of the computer-generated three-dimensional deformable object. Embodiments include associating the two-dimensional signature with the known pose of the computer-generated three-dimensional deformable object. Embodiments include determining a respective pose of an actual three-dimensional deformable object based on an image of the actual three-dimensional deformable object and the associating.

Abstract: A method for creating 2D images of an object with annotation points, the method being carried out by a processing unit and including: considering a synthetic 3D model of the object, named synthetic object, with annotation points correctly placed on the synthetic object; generating several synthetic objects with different poses and different brightness conditions; considering several 2D images with different backgrounds and different brightness conditions; and for each 2D image, insertion of a generated synthetic object in the 2D image.