Abstract: A computer-implemented method of changing a face within an output image or video frame that includes: receiving an input image that includes a face presenting a facial expression in a pose; processing the image with a neural network encoder to generate a latent space point that is an encoded representation of the image; decoding the latent space point to generate an initial output image in accordance with a desired facial identity but with the facial expression and pose of the face in the input image; identifying a feature of the facial expression in the initial output image to edit; applying an adjustment vector to a latent space point corresponding to the initial output image to generate an adjusted latent space point; and decoding the adjusted latent space point to generate an adjusted output image in accordance with the desired facial identity but with the facial expression and pose of the face in the input image altered in accordance with the adjustment vector.

Abstract: Methods, non-transitory machine-readable media, and computing devices for transitioning tasks and interrupt service routines are provided. An example method includes processing, by a plurality of processor cores of a storage controller, tasks and interrupt service routines. A performance statistic is determined corresponding to the plurality of processor cores. Based on detecting that the performance statistic passes a threshold, a number of the plurality of processor cores that are assigned to the tasks and the interrupt service routines are reduced.

Abstract: Various embodiments set forth systems and techniques for changing a face within an image. The techniques include receiving a first image including a face associated with a first facial identity; generating, via a machine learning model, at least a first texture map and a first position map based on the first image; rendering a second image including a face associated with a second facial identity based on the first texture map and the first position map, wherein the second facial identity is different from the first facial identity.

Abstract: The present invention sets forth a technique for analyzing a generative output of a generative model. The technique includes determining a first latent representation of the generative output and a plurality of latent representations of a plurality of data samples associated with the generative model. The technique also includes computing a plurality of similarities between the first latent representation and the plurality of latent representations. In response to determining that a first similarity that is included in the plurality of similarities and computed between the first latent representation and a second latent representation included in the plurality of latent representations exceeds a threshold, the technique includes causing output to be generated that indicates a high similarity between the generative output and a first data sample that is included in the plurality of data samples and corresponds to the second latent representation.

Abstract: Various embodiments set forth systems and techniques for evaluating media content items. The techniques include receiving visual feedback associated with one or more audience members viewing a first media content item; analyzing the visual feedback to generate one or more emotion signals based on the visual feedback; and generating a set of features associated with the one or more audience members viewing the first media content item based on the one or more emotion signals.

Abstract: One embodiment of the present invention sets forth a technique for synthesizing an interaction with a virtual character. The technique includes matching a first message from a user to a first set of memories associated with the virtual character and determining at least a portion of the first set of memories based on a plurality of factors associated with the first set of memories. The technique also includes inputting a first prompt that includes (i) one or more instructions associated with the virtual character, (ii) the at least a portion of the first set of memories, and (iii) the first message into a machine learning model. The technique further includes generating, via execution of the machine learning model based on the first prompt, a first response by the virtual character to the first message, and causing the first response to be outputted to the user.

Abstract: An apparatus for reducing torque in a drill string includes a clamp assembly having a first clamp segment and a second clamp segment, the first and second clamp segments each being generally arcuate and configured to connect together so as to secure the clamp assembly around an oilfield tubular and prevent the clamp assembly from axial and rotational movement relative to the oilfield tubular. The first and second clamp segments each include a first extension and a second extension, each of the first and second extensions having a tapered end that decreases in outer diameter as proceeding in an axial direction, so as to provide a conical guide surface. An outer sleeve is positioned around the clamp assembly, is configured to rotate with respect to the oilfield tubular and the clamp assembly, and is prevented from axial movement relative thereto.

Abstract: Various embodiments set forth systems and techniques for changing a face within an image. The techniques include receiving a first image including a face associated with a first facial identity; generating, via a machine learning model, at least a first texture map and a first position map based on the first image; rendering a second image including a face associated with a second facial identity based on the first texture map and the first position map, wherein the second facial identity is different from the first facial identity.

Abstract: Devices, methods, and systems are provided for placing an implant into a patient and removing it therefrom.

Abstract: Systems and methods are described herein for improvements to generating improved processing pathway management and determining optimal processing increments to complete the processing pathway using synthetic subsets of processing increments. For example, systems and methods are described herein for generating synthetic subsets of processing increments using models and algorithms.

Abstract: One embodiment of the present invention sets forth a technique for performing face swapping. The technique includes converting a first input image that depicts a first facial identity from a first viewpoint at a first time into a first latent representation and converting a second input image that depicts the first facial identity from a second viewpoint at the first time into a second latent representation. The technique also includes generating, via a first machine learning model, a first output image that depicts a second facial identity from the first viewpoint based on the first latent representation. The technique further includes generating, via the first machine learning model, a second output image that depicts the second facial identity from the second viewpoint based on the second latent representation.

Abstract: A portable catwalk sensing device includes a proximity detector configured to detect a proximity of a conveyor portion of a catwalk tubular transport machine, a tubular carried by the catwalk tubular transport machine, or both, to a predetermined location relative to the rig floor. The device also includes a module having a processor, and configured to communicate with the proximity detector and receive data representing proximity of the catwalk tubular transport machine, the tubular, or both from the proximity detector, a rig floor, or a combination thereof. The module includes a housing and is configured to be portable. The device also includes an alarm coupled to or integral with the module. The alarm is configured to communicate with the processor, such that the processor is configured to cause the alarm to provide an indication to a user of the proximity of the catwalk tubular transport machine, the tubular, or both.

Abstract: A system for laying pipe includes a conveyor configured to receive one or more pipes, and one or more friction stir welding (FSW) machines configured to connect the one or more pipes to a pipeline deployed toward a sea floor.

Abstract: Techniques are disclosed for characterizing audience engagement with one or more characters in a media content item. In some embodiments, an audience engagement characterization application processes sensor data; such as video data capturing the faces of one or more audience members consuming a media content item, to generate an audience emotion signal. The characterization application also processes the media content item to generate a character emotion signal associated with one or more characters in the media content item. Then, the characterization application determines an audience engagement score based on an amount of alignment and/or misalignment between the audience emotion signal and the character emotion signal.

Abstract: One embodiment of the present invention sets forth a technique for performing identity-preserving image generation. The technique includes converting an identity image depicting a facial identity into an identity embedding. The technique further includes generating a combined embedding based on the identity embedding and a diffusion iteration identifier. The technique further includes converting, using a neural network and based on the combined embedding, a first input image that includes first noise into a first predicted image depicting one or more facial features that include one or more first facial identity features, wherein the one or more first facial identity features correspond to one or more respective second facial identity features of the identity image and are based at least on the identity embedding.

Abstract: One embodiment of the present invention sets forth a technique for performing face swapping. The technique includes generating a latent representation of a first facial identity included in an input image. The technique further includes identifying a first identity-specific neural network layer associated with a second facial identity from a plurality of identity-specific neural network layers, wherein each neural network layer included in the plurality of identity-specific neural network layers is associated with a different facial identity. The technique further includes executing the first identity-specific neural network layer and one or more other neural network layers to generate one or more decoder input values corresponding to the latent representation. The technique further includes executing a decoder neural network that converts the one or more decoder input values into an output image depicting the second facial identity.

Abstract: A computer-implemented method of changing a face within an output image or video frame that includes: receiving an input image that includes a face presenting a facial expression in a pose; processing the image with a neural network encoder to generate a latent space point that is an encoded representation of the image; decoding the latent space point to generate an initial output image in accordance with a desired facial identity but with the facial expression and pose of the face in the input image; identifying a feature of the facial expression in the initial output image to edit; applying an adjustment vector to a latent space point corresponding to the initial output image to generate an adjusted latent space point; and decoding the adjusted latent space point to generate an adjusted output image in accordance with the desired facial identity but with the facial expression and pose of the face in the input image altered in accordance with the adjustment vector

Abstract: A computer-implemented method of changing a face within an output image or video frame includes: receiving an input image that includes a face presenting a facial expression in a pose; separately encoding different portions of the image by, for each separately encoded portion, generating a latent space point of the portion, thereby generating a plurality of multi-dimensional vectors where each multi-dimensional vector is an encoded representation of a different portion of the input image; concatenating the plurality of multi-dimensional vectors into a combined latent space vector; and decoding the combined latent space vector to generate the output image in accordance with a desired facial identity but with the facial expression and pose of the face in the input image

Abstract: Various embodiments set forth systems and techniques for evaluating media content items. The techniques include receiving visual feedback associated with one or more audience members viewing a first media content item; analyzing the visual feedback to generate one or more emotion signals based on the visual feedback; and generating a set of features associated with the one or more audience members viewing the first media content item based on the one or more emotion signals.

Abstract: Techniques are disclosed for characterizing audience engagement with one or more characters in a media content item. In some embodiments, an audience engagement characterization application processes sensor data, such as video data capturing the faces of one or more audience members consuming a media content item, to generate an audience emotion signal. The characterization application also processes the media content item to generate a character emotion signal associated with one or more characters in the media content item. Then, the characterization application determines an audience engagement score based on an amount of alignment and/or misalignment between the audience emotion signal and the character emotion signal.