Abstract: Obtaining input video data depicting footage of an object, obtaining current values of a set of adjustable parameters of an object representation model comprising a neural network and arranged to generate animated representations of the object using the neural network in which a geometry of the object is controllable by the set of adjustable parameters. For a plurality of iterations, using the object representation model to generate a video layer comprising an animated representation of the object in which the geometry of the object corresponds to the current values of the set of adjustable parameters, presenting composite video data comprising the video layer overlaid on the object in the input video data, and updating the current values of the set of adjustable parameters in response to user input via the user interface.

Abstract: A computer-implemented method of processing target footage of a target human face includes training an encoder-decoder network comprising an encoder network, a first decoder network, and a second decoder network. The training includes training a first path through the encoder-decoder network including the encoder network and the first decoder network to reconstruct the target footage of the target human face, and training a second path through the encoder-decoder network including the encoder network and the second decoder network to process renders of a synthetic face model exhibiting a range of poses and expressions to determine parameter values for the synthetic face model corresponding to the range of poses and expressions. The method includes processing, using a trained network path comprising or trained using the encoder network and comprising the first decoder network, source data representing the synthetic face model exhibiting a source sequence of expressions, to generate output video data.

Abstract: Obtaining input video data depicting footage of an object, obtaining current values of a set of adjustable parameters of an object representation model comprising a neural network and arranged to generate animated representations of the object using the neural network in which a geometry of the object is controllable by the set of adjustable parameters. For a plurality of iterations, using the object representation model to generate a video layer comprising an animated representation of the object in which the geometry of the object corresponds to the current values of the set of adjustable parameters, presenting composite video data comprising the video layer overlaid on the object in the input video data, and updating the current values of the set of adjustable parameters in response to user input via the user interface.

Abstract: A computer implemented method includes receiving, from a remote system, object data comprising values of a set of adjustable parameters of a respective object representation model for each object of a plurality of objects and compositing data indicating at least a respective trajectory of each of the plurality of objects relative to a reference frame. The method includes processing the object data and the compositing data using the respective object representation models to generate output video data depicting a scene including an animated representation of each object of the plurality of objects following the respective trajectory relative to the reference frame. For each object of the plurality of objects, the respective object representation model comprises a respective neural network and is arranged to generate, using the respective neural network, animated representations of the object in which a geometry the object is controllable by the set of adjustable parameters.

Abstract: A computer-implemented method of processing video data comprising a first sequences of image frames containing a first instance of an object. The method includes isolating said first instance of the object within the first sequence of image frames, determining, using the isolated first instance of the object, first parameter values for a synthetic model of the object, modifying the first parameter values for the synthetic model of the object, rendering a modified first instance of the object using a trained machine learning model and the modified first parameter values for the synthetic model of the object, and replacing at least part of the first instance of the object within the first sequence of image frames with a corresponding at least part of the modified first instance of the object.

Abstract: A computer-implemented method of processing target footage of a target human face includes training an encoder-decoder network comprising an encoder network, a first decoder network, and a second decoder network. The training includes training a first path through the encoder-decoder network including the encoder network and the first decoder network to reconstruct the target footage of the target human face, and training a second path through the encoder-decoder network including the encoder network and the second decoder network to process renders of a synthetic face model exhibiting a range of poses and expressions to determine parameter values for the synthetic face model corresponding to the range of poses and expressions. The method includes processing, using a trained network path comprising or trained using the encoder network and comprising the first decoder network, source data representing the synthetic face model exhibiting a source sequence of expressions, to generate output video data.

Abstract: Obtaining input video data depicting footage of an object, obtaining current values of a set of adjustable parameters of an object representation model comprising a neural network and arranged to generate animated representations of the object using the neural network in which a geometry of the object is controllable by the set of adjustable parameters. For a plurality of iterations, using the object representation model to generate a video layer comprising an animated representation of the object in which the geometry of the object corresponds to the current values of the set of adjustable parameters, presenting composite video data comprising the video layer overlaid on the object in the input video data, and updating the current values of the set of adjustable parameters in response to user input via the user interface.

Abstract: An electronic device is provided. The electronic device includes a first antenna which transmits/receives a radio frequency (RF) signal, a second antenna which transmits/receives an RF signal, a third antenna which transmits/receives an RF signal, a first grip sensor sensing a proximity of an external dielectric body, a second grip sensor sensing a proximity of an external dielectric body, a third grip sensor sensing a proximity of an external dielectric body, and a processor operatively connected to the first grip sensor, the second grip sensor, and the third grip sensor, wherein upon sensing proximity of an external dielectric body, the first grip sensor, the second grip sensor, and the third grip sensor transmit proximity information to the processor, and upon receiving proximity information from the second grip sensor and the third grip sensor, the processor determines that an external dielectric body is in proximity to the first grip sensor.

Abstract: A computer-implemented method of processing video data comprising a sequence of image frames. The method includes isolating an instance of an object within the sequence of image frames, generating a modified instance of the object using a machine learning model, and modifying the video data to smoothly transition between at least part of the isolated instance of the object and a corresponding at least part of the modified instance of the object over a subsequence of the sequence of image frames.

Abstract: A computer-implemented method of processing video data comprising a first sequences of image frames containing a first instance of an object. The method includes isolating said first instance of the object within the first sequence of image frames, determining, using the isolated first instance of the object, first parameter values for a synthetic model of the object, modifying the first parameter values for the synthetic model of the object, rendering a modified first instance of the object using a trained machine learning model and the modified first parameter values for the synthetic model of the object, and replacing at least part of the first instance of the object within the first sequence of image frames with a corresponding at least part of the modified first instance of the object.

Abstract: A computer-implemented method of processing video data comprising a first sequences of image frames containing a first instance of an object. The method includes isolating said first instance of the object within the first sequence of image frames, determining, using the isolated first instance of the object, first parameter values for a synthetic model of the object, modifying the first parameter values for the synthetic model of the object, rendering a modified first instance of the object using a trained machine learning model and the modified first parameter values for the synthetic model of the object, and replacing at least part of the first instance of the object within the first sequence of image frames with a corresponding at least part of the modified first instance of the object.

Abstract: A computer-implemented method of processing video data comprising a first sequences of image frames containing a first instance of an object. The method includes isolating said first instance of the object within the first sequence of image frames, determining, using the isolated first instance of the object, first parameter values for a synthetic model of the object, modifying the first parameter values for the synthetic model of the object, rendering a modified first instance of the object using a trained machine learning model and the modified first parameter values for the synthetic model of the object, and replacing at least part of the first instance of the object within the first sequence of image frames with a corresponding at least part of the modified first instance of the object.

Abstract: A computer-implemented method of processing target footage of a target human face includes training an encoder-decoder network comprising an encoder network, a first decoder network, and a second decoder network. The training includes training a first path through the encoder-decoder network including the encoder network and the first decoder network to reconstruct the target footage of the target human face, and training a second path through the encoder-decoder network including the encoder network and the second decoder network to process renders of a synthetic face model exhibiting a range of poses and expressions to determine parameter values for the synthetic face model corresponding to the range of poses and expressions. The method includes processing, using a trained network path comprising or trained using the encoder network and comprising the first decoder network, source data representing the synthetic face model exhibiting a source sequence of expressions, to generate output video data.

Abstract: A computer-implemented method includes obtaining source video data comprising a plurality of image frames, and using a face tracker to detect one or more instances of faces within respective sequences of image frames of the source video data. For a first instance of a given face detected within a first sequence of image frames, the method includes determining a framewise location and size of the first instance of the given face in the first sequence of image frames, using a neural renderer to obtain replacement video data comprising a replacement instance of the given face, and using the determined framewise location and size to replace at least part of the first instance of the given face with at least part of the replacement instance of the given face.

Abstract: A computer-implemented method of processing video data comprising a sequence of image frames. The method includes isolating an instance of an object within the sequence of image frames, generating a modified instance of the object using a machine learning model, and modifying the video data to smoothly transition between at least part of the isolated instance of the object and a corresponding at least part of the modified instance of the object over a subsequence of the sequence of image frames.

Abstract: A computer-implemented method of processing video data comprising a first sequences of image frames containing a first instance of an object. The method includes isolating said first instance of the object within the first sequence of image frames, determining, using the isolated first instance of the object, first parameter values for a synthetic model of the object, modifying the first parameter values for the synthetic model of the object, rendering a modified first instance of the object using a trained machine learning model and the modified first parameter values for the synthetic model of the object, and replacing at least part of the first instance of the object within the first sequence of image frames with a corresponding at least part of the modified first instance of the object.

Abstract: A computer-implemented method of processing video data comprising a first sequences of image frames containing a first instance of an object. The method includes isolating said first instance of the object within the first sequence of image frames, determining, using the isolated first instance of the object, first parameter values for a synthetic model of the object, modifying the first parameter values for the synthetic model of the object, rendering a modified first instance of the object using a trained machine learning model and the modified first parameter values for the synthetic model of the object, and replacing at least part of the first instance of the object within the first sequence of image frames with a corresponding at least part of the modified first instance of the object.

Abstract: Various embodiments provide an antenna device that includes: a metal member configured to have a length that contributes to at least a part of an electronic device; a printed circuit board (PCB) configured to be feed-connected to a preset position of the metal member in order to apply the metal member as an antenna radiator; and at least one electronic component electrically connected to a position different from the feeding position of the metal member and grounded to the PCB, and provide an electronic device that includes the same. Accordingly, the antenna device is grounded to the PCB in a desired position of the metal member by using the basically provided electronic component so that it is possible to exclude a separate electrical connection member, thereby reducing the cost, increasing the use of space, enhancing the degree of freedom of the design of the antenna radiator.

Abstract: Various embodiments provide an antenna device that includes: a metal member configured to have a length that contributes to at least a part of an electronic device; a printed circuit board (PCB) configured to be feed-connected to a preset position of the metal member in order to apply the metal member as an antenna radiator; and at least one electronic component electrically connected to a position different from the feeding position of the metal member and grounded to the PCB, and provide an electronic device that includes the same. Accordingly, the antenna device is grounded to the PCB in a desired position of the metal member by using the basically provided electronic component so that it is possible to exclude a separate electrical connection member, thereby reducing the cost, increasing the use of space, enhancing the degree of freedom of the design of the antenna radiator.

Abstract: Various embodiments provide an antenna device that includes: a metal member configured to have a length that contributes to at least a part of an electronic device; a printed circuit board (PCB) configured to be feed-connected to a preset position of the metal member in order to apply the metal member as an antenna radiator; and at least one electronic component electrically connected to a position different from the feeding position of the metal member and grounded to the PCB, and provide an electronic device that includes the same. Accordingly, the antenna device is grounded to the PCB in a desired position of the metal member by using the basically provided electronic component so that it is possible to exclude a separate electrical connection member, thereby reducing the cost, increasing the use of space, enhancing the degree of freedom of the design of the antenna radiator.