Abstract: A system includes a hardware processor and a memory storing software code. The hardware processor executes the software code to receive a three-dimensional (3-D) image including a plurality of pixels each having a plurality of bins with respective depth values, select, for a first bin of the plurality of bins of a first pixel, a second bin in each of one or more nearest neighbor pixels of the first pixel, the second bin in each of the one or more nearest neighbor pixels having a most similar depth value to a depth value of the first bin. The hardware processor further executes the software code to generate a first depth-aware bin group including the first bin and the second bin in each of the one or more nearest neighbor pixels, and process, using the first depth-aware bin group, the 3-D image to produce a corresponding 3-D output image.

Abstract: A system includes a pre-processor configured to receive three-dimensional (3-D) image data, flatten the 3-D image data to produce corresponding two-dimensional (2-D) image data, and concatenate the 3-D image data and the corresponding 2-D image data to provide concatenated image data. The system further includes an encoder including one or more first neural networks (NNs), the encoder configured to use the one or more first NNs to encode the concatenated image data to provide encoded data, a decoder including one or more second NNs, the decoder configured to use the one or more second NNs to decode the encoded data to provide decoded data, and a reconstructor including a plurality of hybrid 2-D/3-D reconstructors configured to reconstruct the decoded data to provide a denoised 3-D output image corresponding to the 3-D image data.

Abstract: A system includes a hardware processor and a memory storing software code. The hardware processor executes the software code to receive a three-dimensional (3-D) image including a plurality of pixels each having a plurality of bins with respective depth values, select, for a first bin of the plurality of bins of a first pixel, a second bin in each of one or more nearest neighbor pixels of the first pixel, the second bin in each of the one or more nearest neighbor pixels having a most similar depth value to a depth value of the first bin. The hardware processor further executes the software code to generate a first depth-aware bin group including the first bin and the second bin in each of the one or more nearest neighbor pixels, and process, using the first depth-aware bin group, the 3-D image to produce a corresponding 3-D output image.

Abstract: A system includes a pre-processor configured to receive three-dimensional (3-D) image data, flatten the 3-D image data to produce corresponding two-dimensional (2-D) image data, and concatenate the 3-D image data and the corresponding 2-D image data to provide concatenated image data. The system further includes an encoder including one or more first neural networks (NNs), the encoder configured to use the one or more first NNs to encode the concatenated image data to provide encoded data, a decoder including one or more second NNs, the decoder configured to use the one or more second NNs to decode the encoded data to provide decoded data, and a reconstructor including a plurality of hybrid 2-D/3-D reconstructors configured to reconstruct the decoded data to provide a denoised 3-D output image corresponding to the 3-D image data.

Abstract: There is provided a system and method for augmented reality image transformation. In one implementation, such a system includes a system processor, a system memory, and an image transformation engine stored in the system memory. The system processor is configured to execute the image transformation engine to receive image data corresponding to an image, to detect a feature on a surface of the image, and to synthesize a texture corresponding to the feature. The system processor is further configured to execute the image transformation engine to produce an augmented reality representation of the image having the texture for display to a user, the texture covering a surface of the augmented reality representation of the image corresponding to a portion of the feature that is not visible on the surface of the image.

Abstract: There is provided a system and method for augmented reality image transformation. In one implementation, such a system includes a system processor, a system memory, and an image transformation engine stored in the system memory. The system processor is configured to execute the image transformation engine to receive image data corresponding to an image, to detect a feature on a surface of the image, and to synthesize a texture corresponding to the feature. The system processor is further configured to execute the image transformation engine to produce an augmented reality representation of the image having the texture for display to a user, the texture covering a surface of the augmented reality representation of the image corresponding to a portion of the feature that is not visible on the surface of the image.