Abstract: Apparatuses, systems, and techniques to generate pixels based on other pixels. In at least one embodiment, one or more neural networks are used to generate one or more pixels based, at least in part, on sets of pixels surrounding the one or more pixels.

Abstract: Text-to-image generation generally refers to the process of generating an image from one or more text prompts input by a user. While artificial intelligence has been a valuable tool for text-to-image generation, current artificial intelligence-based solutions are more limited as it relates to text-to-3D content creation. For example, these solutions are oftentimes category-dependent, or synthesize 3D content at a low resolution. The present disclosure provides a process and architecture for high-resolution text-to-3D content creation.

Abstract: A method of tracking immune cells to detect immune response. The method including steps of identifying a patient having a disease associated with an organ; administering biocompatible magnetic nanoparticles into the blood stream of the patient; and obtaining a magnetic resonance image of the organ. The presence of hyperintense or hypointense spots in the magnetic resonance image indicates immune response in the patient.

Abstract: The present disclosure relates to an image composite system that employs a generative adversarial network to generate realistic composite images. For example, in one or more embodiments, the image composite system trains a geometric prediction neural network using an adversarial discrimination neural network to learn warp parameters that provide correct geometric alignment of foreground objects with respect to a background image. Once trained, the determined warp parameters provide realistic geometric corrections to foreground objects such that the warped foreground objects appear to blend into background images naturally when composited together.

Abstract: Techniques are disclosed for 3D object reconstruction using photometric mesh representations. A decoder is pretrained to transform points sampled from 2D patches of representative objects into 3D polygonal meshes. An image frame of the object is fed into an encoder to get an initial latent code vector. For each frame and camera pair from the sequence, a polygonal mesh is rendered at the given viewpoints. The mesh is optimized by creating a virtual viewpoint, rasterized to obtain a depth map. The 3D mesh projections are aligned by projecting the coordinates corresponding to the polygonal face vertices of the rasterized mesh to both selected viewpoints. The photometric error is determined from RGB pixel intensities sampled from both frames. Gradients from the photometric error are backpropagated into the vertices of the assigned polygonal indices by relating the barycentric coordinates of each image to update the latent code vector.

Abstract: Techniques are disclosed for 3D object reconstruction using photometric mesh representations. A decoder is pretrained to transform points sampled from 2D patches of representative objects into 3D polygonal meshes. An image frame of the object is fed into an encoder to get an initial latent code vector. For each frame and camera pair from the sequence, a polygonal mesh is rendered at the given viewpoints. The mesh is optimized by creating a virtual viewpoint, rasterized to obtain a depth map. The 3D mesh projections are aligned by projecting the coordinates corresponding to the polygonal face vertices of the rasterized mesh to both selected viewpoints. The photometric error is determined from RGB pixel intensities sampled from both frames. Gradients from the photometric error are backpropagated into the vertices of the assigned polygonal indices by relating the barycentric coordinates of each image to update the latent code vector.

Abstract: The present disclosure relates to an image composite system that employs a generative adversarial network to generate realistic composite images. For example, in one or more embodiments, the image composite system trains a geometric prediction neural network using an adversarial discrimination neural network to learn warp parameters that provide correct geometric alignment of foreground objects with respect to a background image. Once trained, the determined warp parameters provide realistic geometric corrections to foreground objects such that the warped foreground objects appear to blend into background images naturally when composited together.

Abstract: Techniques are disclosed for 3D object reconstruction using photometric mesh representations. A decoder is pretrained to transform points sampled from 2D patches of representative objects into 3D polygonal meshes. An image frame of the object is fed into an encoder to get an initial latent code vector. For each frame and camera pair from the sequence, a polygonal mesh is rendered at the given viewpoints. The mesh is optimized by creating a virtual viewpoint, rasterized to obtain a depth map. The 3D mesh projections are aligned by projecting the coordinates corresponding to the polygonal face vertices of the rasterized mesh to both selected viewpoints. The photometric error is determined from RGB pixel intensities sampled from both frames. Gradients from the photometric error are backpropagated into the vertices of the assigned polygonal indices by relating the barycentric coordinates of each image to update the latent code vector.

Abstract: The present disclosure relates to an image composite system that employs a generative adversarial network to generate realistic composite images. For example, in one or more embodiments, the image composite system trains a geometric prediction neural network using an adversarial discrimination neural network to learn warp parameters that provide correct geometric alignment of foreground objects with respect to a background image. Once trained, the determined warp parameters provide realistic geometric corrections to foreground objects such that the warped foreground objects appear to blend into background images naturally when composited together.

Abstract: The present disclosure relates to an image composite system that employs a generative adversarial network to generate realistic composite images. For example, in one or more embodiments, the image composite system trains a geometric prediction neural network using an adversarial discrimination neural network to learn warp parameters that provide correct geometric alignment of foreground objects with respect to a background image. Once trained, the determined warp parameters provide realistic geometric corrections to foreground objects such that the warped foreground objects appear to blend into background images naturally when composited together.

Abstract: A method of treating a condition related to iron deficiency. The method includes steps of identifying a patient having a condition related to iron deficiency and administering an effective amount of biocompatible iron oxide nanoparticles to the patient. The biocompatible iron oxide nanoparticles each contains an iron oxide core that is covered by one or more biocompatible polymers, each of which has a polyethylene glycol group, a silane group, and a linker linking, via a covalent bond, the polyethylene glycol group and the silane group.

Abstract: A method of treating a condition related to iron deficiency. The method includes steps of identifying a patient having a condition related to iron deficiency and administering an effective amount of biocompatible iron oxide nanoparticles to the patient. The biocompatible iron oxide nanoparticles each contains an iron oxide core that is covered by one or more biocompatible polymers, each of which has a polyethylene glycol group, a silane group, and a linker linking, via a covalent bond, the polyethylene glycol group and the silane group.

Abstract: A method of tracking immune cells to detect immune response. The method including steps of identifying a patient having a disease associated with an organ; administering biocompatible magnetic nanoparticles into the blood stream of the patient; and obtaining a magnetic resonance image of the organ. The presence of hyperintense or hypointense spots in the magnetic resonance image indicates immune response in the patient.

Abstract: The present invention relates to a polarized light emitting diode (LED) device and the method for manufacturing the same, in which the LED device comprises: a base, a light emitting diode (LED) chip, a polarizing waveguide and a packaging material. In an exemplary embodiment, the LED chip is disposed on the base and is configured with a first light-emitting surface for outputting light therefrom; and the waveguide, being comprised of a polarization layer, a reflection layer, a conversion layer and a light transmitting layer, is disposed at the optical path of the light emitted from the LED chip; and the packaging material is used for packaging the waveguide, the LED chip and the base into a package.

Abstract: An herbal extract which induces immune cells to produce interferon and activates Toll-like receptors and a preparation method thereof are provided. The herbal extract is extracted from an effective amount of raw material including Glycyrrhizae Radix, Bupleuri Radix, Scutellariae Radix, Schisandrae Fructus and Paeoniae Rubra Radix. Glycyrrhizae Radix, Bupleuri Radix, Scutellariae Radix, Schisandrae Fructus and Paeoniae Rubra Radix have a weight ratio of 1-5:1-5:1-5:1-3:1-3.