A method of point cloud attribute coding includes obtaining an attribute signal corresponding to a point cloud; determining whether lossless lifting is enabled; based on determining that lossless lifting is enabled, modifying at least one from among a plurality of quantization weight and a plurality of lifting coefficients; decomposing the attribute signal into a plurality of detail signals and a plurality of approximation signals based on the modified at least one from among the plurality of quantization weights and the plurality of lifting coefficients; generating a bitstream representing the point cloud based on the plurality of detail signals and the plurality of approximation signals; and transmitting the bitstream.

A method of point cloud attribute coding includes obtaining an attribute signal corresponding to a point cloud; determining whether lossless lifting is enabled; based on determining that lossless lifting is enabled, modifying at least one from among a plurality of quantization weight and a plurality of lifting coefficients; decomposing the attribute signal into a plurality of detail signals and a plurality of approximation signals based on the modified at least one from among the plurality of quantization weights and the plurality of lifting coefficients; generating a bitstream representing the point cloud based on the plurality of detail signals and the plurality of approximation signals; and transmitting the bitstream.

Techniques for lossless compression of a digital image using prior image context.

A method for deblurring a blurred image includes encoding, by at least one processor, a blurred image at a plurality of stages of encoding to obtain an encoded image at each of the plurality of stages; decoding, by the at least one processor, an encoded image obtained from a final stage of the plurality of stages of encoding by using an encoding feedback from each of the plurality of stages and a machine learning (ML) feedback from at least one ML model; and generating, by the at least one processor, a deblurred image in which at least one portion of the blurred image is deblurred based on a result of the decoding.

A technique for compressing an original image is disclosed. According to the technique, an original image is obtained and a delta-encoded image is generated based on the original image. Next, a segregated image is generated based on the delta-encoded image and then the segregated image is compressed to produce a compressed image. The segregated image is generated because the segregated image may be compressed more efficiently than the original image and the delta image.

A technique for compressing an original image is disclosed. According to the technique, an original image is obtained and a delta-encoded image is generated based on the original image. Next, a segregated image is generated based on the delta-encoded image and then the segregated image is compressed to produce a compressed image. The segregated image is generated because the segregated image may be compressed more efficiently than the original image and the delta image.

Techniques are disclosed for changing the identities of faces in images. In embodiments, a tunable model for changing facial identities in images includes an encoder, a decoder, and dense layers that generate either adaptive instance normalization (AdaIN) coefficients that control the operation of convolution layers in the decoder or the values of weights within such convolution layers, allowing the model to change the identity of a face in an image based on a user selection. A separate set of dense layers may be trained to generate AdaIN coefficients for each of a number of facial identities, and the AdaIN coefficients output by different sets of dense layers can be combined to interpolate between facial identities. Alternatively, a single set of dense layers may be trained to take as input an identity vector and output AdaIN coefficients or values of weighs within convolution layers of the decoder.

Techniques are disclosed for changing the identities of faces in images. In embodiments, a tunable model for changing facial identities in images includes an encoder, a decoder, and dense layers that generate either adaptive instance normalization (AdaIN) coefficients that control the operation of convolution layers in the decoder or the values of weights within such convolution layers, allowing the model to change the identity of a face in an image based on a user selection. A separate set of dense layers may be trained to generate AdaIN coefficients for each of a number of facial identities, and the AdaIN coefficients output by different sets of dense layers can be combined to interpolate between facial identities. Alternatively, a single set of dense layers may be trained to take as input an identity vector and output AdaIN coefficients or values of weighs within convolution layers of the decoder.

An encoding method and a decoding method. The encoding method includes generating curved image by creating projection of visual scene onto inner surface of imaginary 3D geometric shape that is curved in at least one dimension; dividing curved image into input portion and plurality of input rings; encoding input portion and input rings into first planar image and second planar image, respectively, such that input portion is stored into first planar image, and input rings are packed into corresponding rows of second planar image; and communicating, to display apparatus, first and second planar images and information indicative of sizes of input portion and input rings.

An encoding method and a decoding method. The encoding method includes generating curved image by creating projection of visual scene onto inner surface of imaginary 3D geometric shape that is curved in at least one dimension; dividing curved image into input portion and plurality of input rings; encoding input portion and input rings into first planar image and second planar image, respectively, such that input portion is stored into first planar image, and input rings are packed into corresponding rows of second planar image; and communicating, to display apparatus, first and second planar images and information indicative of sizes of input portion and input rings.