Abstract: Techniques related to automatically segmenting video frames into per pixel fidelity object of interest and background regions are discussed. Such techniques include applying tessellation to a video frame to generate feature frames corresponding to the video frame and applying a segmentation network implementing context aware skip connections to an input volume including the feature frames and a context feature volume corresponding to the video frame to generate a segmentation for the video frame.

Abstract: An article of footwear includes an upper, a sole structure coupled to the upper, at least one receiver integrated into an exterior surface of the upper, and a removable shield configured to selectively attach to the at least one receiver. The removable shield has an outward-facing ornamental exterior surface when attached to the at least one receiver.

Abstract: Gesture-controlled virtual reality systems and methods of controlling the same are disclosed herein. An example apparatus includes an on-body sensor to output first signals associated with at least one of movement of a body part of a user or a position of the body part relative to a virtual object and an off-body sensor to output second signals associated with at least one of the movement or the position relative to the virtual object. The apparatus also includes at least one processor to generate gesture data based on at least one of the first or second signals, generate position data based on at least one of the first or second signals, determine an intended action of the user relative to the virtual object based on the position data and the gesture data, and generate an output of the virtual object in response to the intended action.

Abstract: Gesture-controlled virtual reality systems and methods of controlling the same are disclosed herein. An example apparatus includes an on-body sensor to output first signals associated with at least one of movement of a body part of a user or a position of the body part relative to a virtual object and an off-body sensor to output second signals associated with at least one of the movement or the position relative to the virtual object. The apparatus also includes at least one processor to generate gesture data based on at least one of the first or second signals, generate position data based on at least one of the first or second signals, determine an intended action of the user relative to the virtual object based on the position data and the gesture data, and generate an output of the virtual object in response to the intended action.

Abstract: A method for displaying game-related images on footwear with integrated or coupled display devices. The method includes authenticating user credentials with a video game platform, querying the platform for game-related images associated with the user's profile, and receiving a user-selected image. The selected image is processed for display on the footwear's display device. A communication link is established between a computing device and the display device, and the processed image is transmitted and displayed. The method further involves receiving a unique article identifier from communication circuitry associated with the display device and recording an association between the displayed image and the article identifier.

Abstract: A method for displaying and managing digital collectables on wearable articles with integrated displays. The method involves receiving a digital collectable at a computing device and transmitting it to a wearable article for display on an integrated display. An identifier unique to the wearable article is received, and an association between the digital collectable and the wearable article identifier is recorded. The method further includes receiving information related to the usage of the wearable article while displaying the digital collectable. Based on this received information, metadata for the digital collectable is generated. The generated metadata is then recorded in association with the digital collectable.

Abstract: Methods, systems, and apparatus for high-fidelity vision tasks using deep neural networks are disclosed. An example apparatus includes a feature extractor to extract low-level features and edge-enhanced features of an input image processed using a convolutional neural network, an eidetic memory block generator to generate an eidetic memory block using the extracted low-level features or the extracted edge-enhanced features, and an interactive segmentation network to perform image segmentation using the eidetic memory block, the eidetic memory block used to propagate domain-persistent features through the segmentation network.

Abstract: Various embodiments are generally directed to techniques for image segmentation utilizing context, such as with a machine learning (ML) model that injects context into various training stages. Many embodiments utilize one or more of an encoder-decoder model topology and select criteria and parameters in hyper-parameter optimization (HPO) to conduct the best model neural architecture search (NAS). Some embodiments are particularly directed to resizing context frames to a resolution that corresponds with a particular stage of decoding. In several embodiments, the context frames are concatenated with one or more of data from a previous decoding stage and data from a corresponding encoding stage prior to being provided as input to a next decoding stage.

Abstract: A method of displaying a cryptographically secured digital collectable on a digital display includes receiving the cryptographically secured digital collectable; receiving an indication from a user to display the cryptographically secured digital collectable on the digital display provided on an article of footwear or apparel; receiving an article identifier from communication circuitry provided on the article of footwear in response to receiving the indication to display the digital collectable on the article of footwear or apparel; transmitting the cryptographically secured digital collectable to the article of footwear or apparel for display on the digital display; and recording or requesting the recordation that the cryptographically secured digital collectable is displayed in connection with the article identifier of the article of footwear or apparel.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed for interactive image segmentation. An example apparatus includes an inception controller to execute an inception sublayer of a convolutional neural network (CNN) including two or more inception-atrous-collation (IAC) layers, the inception sublayer including two or more convolutions including respective kernels of varying sizes to generate multi-scale inception features, the inception sublayer to receive one or more context features indicative of user input; an atrous controller to execute an atrous sublayer of the CNN, the atrous sublayer including two or more atrous convolutions including respective kernels of varying sizes to generate multi-scale atrous features; and a collation controller to execute a collation sublayer of the CNN to collate the multi-scale inception features, the multi-scale atrous features, and eidetic memory features.

Abstract: Methods, systems and apparatuses may provide for technology that trains a neural network by inputting video data to the neural network, determining a boundary loss function for the neural network, and selecting weights for the neural network based at least in part on the boundary loss function, wherein the neural network outputs a pixel-level segmentation of one or more objects depicted in the video data. The technology may also operate the neural network by accepting video data and an initial feature set, conducting a tensor decomposition on the initial feature set to obtain a reduced feature set, and outputting a pixel-level segmentation of object(s) depicted in the video data based at least in part on the reduced feature set.

Abstract: An athletic performance monitoring system, including a gesture recognition processor configured to execute gesture recognition processes. Interaction with the athletic performance monitoring system may be based, at least in part, on gestures performed by a user, and may offer an alternative to making selections on the athletic performance monitoring system using physical buttons, which may be cumbersome and/or inconvenient to use while performing an athletic activity. Additionally, recognized gestures may be used to select one or more operational modes for the athletic performance monitoring system, such that a reduction in power consumption may be achieved.

Abstract: Techniques related to automatically segmenting video frames into per pixel fidelity object of interest and background regions are discussed. Such techniques include applying tessellation to a video frame to generate feature frames corresponding to the video frame and applying a segmentation network implementing context aware skip connections to an input volume including the feature frames and a context feature volume corresponding to the video frame to generate a segmentation for the video frame.

Abstract: Techniques related to automatically segmenting video frames into per pixel fidelity object of interest and background regions are discussed. Such techniques include applying tessellation to a video frame to generate feature frames corresponding to the video frame and applying a segmentation network implementing context aware skip connections to an input volume including the feature frames and a context feature volume corresponding to the video frame to generate a segmentation for the video frame.

Abstract: Methods, systems and apparatuses may provide for technology that trains a neural network by inputting video data to the neural network, determining a boundary loss function for the neural network, and selecting weights for the neural network based at least in part on the boundary loss function, wherein the neural network outputs a pixel-level segmentation of one or more objects depicted in the video data. The technology may also operate the neural network by accepting video data and an initial feature set, conducting a tensor decomposition on the initial feature set to obtain a reduced feature set, and outputting a pixel-level segmentation of object(s) depicted in the video data based at least in part on the reduced feature set.

Abstract: A method of displaying a cryptographically secured digital collectable on a digital display includes receiving the cryptographically secured digital collectable; receiving an indication from a user to display the cryptographically secured digital collectable on the digital display provided on an article of footwear or apparel; receiving an article identifier from communication circuitry provided on the article of footwear in response to receiving the indication to display the digital collectable on the article of footwear or apparel; transmitting the cryptographically secured digital collectable to the article of footwear or apparel for display on the digital display; and recording or requesting the recordation that the cryptographically secured digital collectable is displayed in connection with the article identifier of the article of footwear or apparel.

Abstract: An athletic performance monitoring system, including a gesture recognition processor configured to execute gesture recognition processes. Interaction with the athletic performance monitoring system may be based, at least in part, on gestures performed by a user, and may offer an alternative to making selections on the athletic performance monitoring system using physical buttons, which may be cumbersome and/or inconvenient to use while performing an athletic activity. Additionally, recognized gestures may be used to select one or more operational modes for the athletic performance monitoring system, such that a reduction in power consumption may be achieved.

Abstract: Techniques related to automatically segmenting a video frame into fine grain object of interest and background regions using a ground truth segmentation of an object in a previous frame are discussed. Such techniques apply multiple levels of segmentation tracking and prediction based on color, shape, and motion of the segmentation to determine per-pixel object probabilities, and solve an energy summation model to generate a final segmentation for the video frame using the object probabilities.

Abstract: Techniques related to automatically segmenting video frames into per pixel dense object of interest and background regions are discussed. Such techniques include applying a segmentation convolutional neural network (CNN) to a CNN input including a current video frame, a previous video frame, an object of interest indicator frame, a motion frame, and multiple feature frames each including features compressed from feature layers of an object classification convolutional neural network as applied to the current video frame to generate candidate segmentations and selecting one of the candidate segmentations as a final segmentation of the current video frame.

Abstract: Techniques related to automatically segmenting a video frame into fine grain object of interest and background regions using a ground truth segmentation of an object in a previous frame are discussed. Such techniques apply multiple levels of segmentation tracking and prediction based on color, shape, and motion of the segmentation to determine per-pixel object probabilities, and solve an energy summation model to generate a final segmentation for the video frame using the object probabilities.