Abstract: A method of training a neural network model to generate a three-dimensional (3D) model of a scene includes: generating the 3D model based on a latent code; based on the 3D model, sampling a camera view including a camera position and a camera angle corresponding to the 3D model of the scene; generating a two-dimensional (2D) image based on the 3D model and the sampled camera view; and training the neural network model to, using the 3D model, generate a scene corresponding to the sampled camera view based on the generated 2D image and a real 2D image.

Abstract: Matching an illumination of an embedded virtual object (VO) with current environment illumination conditions provides an enhanced immersive experience to a user. To match the VO and environment illuminations, illumination basis functions are determined based on preprocessing image data, captured as a first combination of intensities of direct illumination sources illuminates the environment. Each basis function corresponds to one of the direct illumination sources. During the capture of runtime image data, a second combination of intensities illuminates the environment. An illumination-weighting vector is determined based on the runtime image data. The determination of the weighting vector accounts for indirect illumination sources, such as surface reflections. The weighting vector encodes a superposition of the basis functions that corresponds to the second combination of intensities. The method illuminates the VO based on the weighting vector.

Abstract: Matching an illumination of an embedded virtual object (VO) with current environment illumination conditions provides an enhanced immersive experience to a user. To match the VO and environment illuminations, illumination basis functions are determined based on preprocessing image data, captured as a first combination of intensities of direct illumination sources illuminates the environment. Each basis function corresponds to one of the direct illumination sources. During the capture of runtime image data, a second combination of intensities illuminates the environment. An illumination-weighting vector is determined based on the runtime image data. The determination of the weighting vector accounts for indirect illumination sources, such as surface reflections. The weighting vector encodes a superposition of the basis functions that corresponds to the second combination of intensities. The method illuminates the VO based on the weighting vector.

Abstract: Matching an illumination of an embedded virtual object (VO) with current environment illumination conditions provides an enhanced immersive experience to a user. To match the VO and environment illuminations, illumination basis functions are determined based on preprocessing image data, captured as a first combination of intensities of direct illumination sources illuminates the environment. Each basis function corresponds to one of the direct illumination sources. During the capture of runtime image data, a second combination of intensities illuminates the environment. An illumination-weighting vector is determined based on the runtime image data. The determination of the weighting vector accounts for indirect illumination sources, such as surface reflections. The weighting vector encodes a superposition of the basis functions that corresponds to the second combination of intensities. The method illuminates the VO based on the weighting vector.

Abstract: Matching an illumination of an embedded virtual object (VO) with current environment illumination conditions provides an enhanced immersive experience to a user. To match the VO and environment illuminations, illumination basis functions are determined based on preprocessing image data, captured as a first combination of intensities of direct illumination sources illuminates the environment. Each basis function corresponds to one of the direct illumination sources. During the capture of runtime image data, a second combination of intensities illuminates the environment. An illumination-weighting vector is determined based on the runtime image data. The determination of the weighting vector accounts for indirect illumination sources, such as surface reflections. The weighting vector encodes a superposition of the basis functions that corresponds to the second combination of intensities. The method illuminates the VO based on the weighting vector.

Abstract: A method of preparing for a positive active material for a rechargeable lithium battery is provided. In this method, a lithiated compound to be coated and an organic solution or aqueous solution including a coating-element source are putted into a mixer, the mixture is continuously stirred to mix the contents thoroughly, and a hot dry gas is introduced into the mixer to evaporate the solvent while the powder is continuously agitated. The resulting dry coated powdery compound is heat-treated at an elevated temperature to obtain an oxide coating on the lithiated compound.

Abstract: A method of preparing for a positive active material for a rechargeable lithium battery is provided. In this method, a lithiated compound to be coated and an organic solution or aqueous solution including a coating-element source are putted into a mixer, the mixture is continuously stirred to mix the contents thoroughly, and a hot dry gas is introduced into the mixer to evaporate the solvent while the powder is continuously agitated. The resulting dry coated powdery compound is heat-treated at an elevated temperature to obtain an oxide coating on the lithiated compound.