Abstract: Variational Autoencoders (VAEs) have been shown to be effective in modeling complex data distributions. Conventional VAEs operate with fully-observed data during training. However, learning a VAE model from partially-observed data is still a problem. A modified VAE framework is proposed that can learn from partially-observed data conditioned on the fully-observed mask. A model described in various embodiments is capable of learning a proper proposal distribution based on the missing data. The framework is evaluated for both high-dimensional multimodal data and low dimensional tabular data.

Abstract: A computer implemented system for generating one or more data structures is described, the one or more data structures representing an unseen composition based on a first category and a second category observed individually in a training data set. During training of a generator, a proposed framework utilizes at least one of the following discriminators—three pixel-centric discriminators, namely, frame discriminator, gradient discriminator, video discriminator; and one object-centric relational discriminator. The three pixel-centric discriminators ensure spatial and temporal consistency across the frames, and the relational discriminator leverages spatio-temporal scene graphs to reason over the object layouts in videos ensuring the right interactions among objects.

Abstract: Variational Autoencoders (VAEs) have been shown to be effective in modeling complex data distributions. Conventional VAEs operate with fully-observed data during training. However, learning a VAE model from partially-observed data is still a problem. A modified VAE framework is proposed that can learn from partially-observed data conditioned on the fully-observed mask. A model described in various embodiments is capable of learning a proper proposal distribution based on the missing data. The framework is evaluated for both high-dimensional multimodal data and low dimensional tabular data.

Abstract: One embodiment provides a method, including: obtaining, at an information handling device, an image of a person; determining physical characteristics of the person by analyzing the image; receiving an image of at least one selected piece of jewelry, the selected jewelry having a given jewelry profile, wherein the jewelry profile describes features and construction of the selected piece of jewelry; overlaying the image of the at least one selected piece of jewelry onto an image of the person, wherein the overlaying comprises analyzing resizing the image of the at least one selected piece of jewelry to match the physical characteristics of the person, in view of the jewelry profile of the at least one selected piece of jewelry; and providing, on a display of the information handling device, an output image of the image of the person comprising the overlaid image of the at least one piece of jewelry.

Abstract: A computer implemented system for generating one or more data structures is described, the one or more data structures representing an unseen composition based on a first category and a second category observed individually in a training data set. During training of a generator, a proposed framework utilizes at least one of the following discriminators—three pixel-centric discriminators, namely, frame discriminator, gradient discriminator, video discriminator; and one object-centric relational discriminator. The three pixel-centric discriminators ensure spatial and temporal consistency across the frames, and the relational discriminator leverages spatio-temporal scene graphs to reason over the object layouts in videos ensuring the right interactions among objects.

Abstract: One embodiment provides a method, including: obtaining, at an information handling device, an image of a person; determining physical characteristics of the person by analyzing the image; receiving an image of at least one selected piece of jewelry, the selected jewelry having a given jewelry profile, wherein the jewelry profile describes features and construction of the selected piece of jewelry; overlaying the image of the at least one selected piece of jewelry onto an image of the person, wherein the overlaying comprises analyzing resizing the image of the at least one selected piece of jewelry to match the physical characteristics of the person, in view of the jewelry profile of the at least one selected piece of jewelry; and providing, on a display of the information handling device, an output image of the image of the person comprising the overlaid image of the at least one piece of jewelry.

Abstract: One embodiment provides a method for location detection using an indoor ceiling pattern within a building, the method including: utilizing at least one processor to execute computer code that performs the steps of: capturing, using an image capture device, an image of the indoor ceiling pattern; identifying, within the image, at least one object; generating, based on the at least one object, a key matrix; determining if the key matrix matches a subset of a known key matrix; and responsive to the determining, identifying, based on the known key matrix, a location of the image capture device within the building. Other aspects are described and claimed.

Abstract: One embodiment provides a method for location detection using an indoor ceiling pattern within a building, the method including: utilizing at least one processor to execute computer code that performs the steps of: capturing, using an image capture device, an image of the indoor ceiling pattern; identifying, within the image, at least one object; generating, based on the at least one object, a key matrix; determining if the key matrix matches a subset of a known key matrix; and responsive to the determining, identifying, based on the known key matrix, a location of the image capture device within the building. Other aspects are described and claimed.