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1. One or more processors, comprising: one or more circuits circuitry to: obtain results of a plurality of physics-based simulations of a physical object performed in one or more different virtual environments using a three-dimensional (3D) model of the physical object, wherein the plurality of physical-based simulations of the physical object comprises applying one or more mathematical models that define one or more states of the one or more different virtual environments and defines physically-realistic laws of physics to the 3D model to generate interactions of the 3D model with respect to one or more other objects in the one or more different virtual environments; and generate, based at least in part on results of the plurality of physics-based simulations applied to the 3D model, a plurality of training data and a plurality of labels corresponding to different configurations resulting from the plurality of physics-based simulations to train a neural network, wherein the plurality of training data comprises training images and labels indicating locations and classifications of one or more objects of the training images, and further wherein the training images comprise a plurality of photorealistic images of the model of the physical object in different poses.
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