Abstract: Systems and methods are provided for receiving, at a server computer, a plurality of content messages from a plurality of content sources, each content message comprising media content and associated with a predetermined media collection, for each of the plurality of content messages received, analyzing each of the plurality of content messages to determine a quality score for each of the plurality of content messages, and storing each of the plurality of content messages in a database along with the quality score for each of the plurality of content messages.

Abstract: A modulated segmentation system can use a modulator network to emphasize spatial prior data of an object to track the object across multiple images. The modulated segmentation system can use a segmentation network that receives spatial prior data as intermediate data that improves segmentation accuracy. The segmentation network can further receive visual guide information from a visual guide network to increase tracking accuracy via segmentation.

Abstract: A machine learning system can generate an image mask (e.g., a pixel mask) comprising pixel assignments for pixels. The pixels can be assigned to classes, including, for example, face, clothes, body skin, or hair. The machine learning system can be implemented using a convolutional neural network that is configured to execute efficiently on computing devices having limited resources, such as mobile phones. The pixel mask can be used to more accurately display video effects interacting with a user or subject depicted in the image.

Abstract: A compact neural network system can generate multiple individual filters from a compound filter. Each convolutional layer of a convolutional neural network can include a compound filters used to generate individual filters for that layer. The individual filters overlap in the compound filter and can be extracted using a sampling operation. The extracted individual filters can share weights with nearby filters thereby reducing the overall size of the convolutional neural network.

Abstract: The present disclosure provides a video processing method, a video processing apparatus, and a storage medium. A picture of the video includes a landmark building and a moving subject. The video processing method includes: identifying and tracking the landmark building in the video; extracting and tracking a key point of the moving subject in the video, and determining a posture of the moving subject based on information of the extracted key point of the moving subject; and making the key point of the moving subject correspond to the landmark building, and driving the landmark building to perform a corresponding action based on an action of the key point of the moving subject, so as to make a posture of the landmark building in the picture of the video correspond to the posture of the moving subject. The video processing method may enhance interactions between the user and the shot landmark.

Abstract: A machine learning system can generate an image mask (e.g., a pixel mask) comprising pixel assignments for pixels. The pixels can be assigned to classes, including, for example, face, clothes, body skin, or hair. The machine learning system can be implemented using a convolutional neural network that is configured to execute efficiently on computing devices having limited resources, such as mobile phones. The pixel mask can be used to more accurately display video effects interacting with a user or subject depicted in the image.

Abstract: A mobile device can generate real-time complex visual image effects using asynchronous processing pipeline. A first pipeline applies a complex image process, such as a neural network, to keyframes of a live image sequence. A second pipeline generates flow maps that describe feature transformations in the image sequence. The flow maps can be used to process non-keyframes on the fly. The processed keyframes and non-keyframes can be used to display a complex visual effect on the mobile device in real-time or near real-time.

Abstract: A mobile device can generate real-time complex visual image effects using asynchronous processing pipeline. A first pipeline applies a complex image process, such as a neural network, to keyframes of a live image sequence. A second pipeline generates flow maps that describe feature transformations in the image sequence. The flow maps can be used to process non-keyframes on the fly. The processed keyframes and non-keyframes can be used to display a complex visual effect on the mobile device in real-time or near real-time.

Abstract: Embodiments of the disclosure provide a method and a device for processing a portrait image, the method includes: acquiring a to-be-processed portrait image; inputting the to-be-processed portrait image into an image processing model, and acquiring a head smear image output by the image processing model, where the image processing model is configured to smear a hair area of a portrait located above a preset boundary in the portrait image, and the image processing model is generated by training a sample data set of a sample portrait image and a sample head smear image corresponding to the sample portrait image; rendering the head smear image with a head effect material to obtain a portrait image added with an effect; and displaying the portrait image added with the effect.

Abstract: A modulated segmentation system can use a modulator network to emphasize spatial prior data of an object to track the object across multiple images. The modulated segmentation system can use a segmentation network that receives spatial prior data as intermediate data that improves segmentation accuracy. The segmentation network can further receive visual guide information from a visual guide network to increase tracking accuracy via segmentation.

Abstract: Systems, devices, methods, media, and instructions for automated image processing and content curation are described. In one embodiment a server computer system receives a plurality of content communications from a plurality of client devices, each content communication comprising an associated piece of content and a corresponding metadata. Each content communication is processed to determine associated context values for each piece of content, each associated context value comprising at least one content value generated by machine vision processing of the associated piece of content. A first content collection is automatically generated based on context values, and a set of user accounts are associated with the collection. An identifier associated with the first content collection is published to user devices associated with user accounts. In various additional embodiments, different content values, image processing operations, and content selection operations are used to curate content collections.

Abstract: Disclosed herein are arrangements that facilitate the transfer of knowledge from models for a source data-processing domain to models for a target data-processing domain. A convolutional neural network space for a source domain is factored into a first classification space and a first reconstruction space. The first classification space stores class information and the first reconstruction space stores domain-specific information. A convolutional neural network space for a target domain is factored into a second classification space and a second reconstruction space. The second classification space stores class information and the second reconstruction space stores domain-specific information. Distribution of the first classification space and the second classification space is aligned.

Abstract: Systems and methods are provided for receiving input increasing a default predetermined window of time that the new media collection is accessible and activating the new media collection for the increased predetermined window of time and a geographic boundary size for where media content originates. The systems and methods further cause a plurality of content messages comprising media content originating in the geographical boundary size to be included in the new media collection and displayed in response to a request from a computing device to view the new media collection based on determining the request occurs within the increased predetermined window of time that the new media collection is accessible.

Abstract: A modulated segmentation system can use a modulator network to emphasize spatial prior data of an object to track the object across multiple images. The modulated segmentation system can use a segmentation network that receives spatial prior data as intermediate data that improves segmentation accuracy. The segmentation network can further receive visual guide information from a visual guide network to increase tracking accuracy via segmentation.

Abstract: A landmark data collection method includes: determining (S100) a first basic collection point (A), a second basic collection point (B), and a third basic collection point (C) sequentially in an observation area of a landmark building; and collecting (S200) photos of the landmark building based on each of the first basic collection point (A), the second basic collection point (B), and the third basic collection point (C) to obtain landmark data of the landmark building. A photo of the landmark building is taken by a camera at the i-th basic collection point; and a collection point is determined at every predetermined distance interval as the camera is moved in a counterclockwise direction and/or a clockwise direction, and the photo of the landmark building is taken by the camera at the collection point, until the camera is moved out of the observation area, where i=1, 2, 3.

Abstract: Systems, devices, media, and methods are presented for object detection and inserting graphical elements into an image stream in response to detecting the object. The systems and methods detect an object of interest in received frames of a video stream. The systems and methods identify a bounding box for the object of interest and estimate a three-dimensional position of the object of interest based on a scale of the object of interest. The systems and methods generate one or more graphical elements having a size based on the scale of the object of interest and a position based on the three-dimensional position estimated for the object of interest. The one or more graphical elements are generated within the video stream to form a modified video stream. The systems and methods cause presentation of the modified video stream including the object of interest and the one or more graphical elements.

Abstract: A compact neural network system can generate multiple individual filters from a compound filter. Each convolutional layer of a convolutional neural network can include a compound filters used to generate individual filters for that layer. The individual filters overlap in the compound filter and can be extracted using a sampling operation. The extracted individual filters can share weights with nearby filters thereby reducing the overall size of the convolutional neural network.

Abstract: A machine learning system can generate an image mask (e.g., a pixel mask) comprising pixel assignments for pixels. The pixels can be assigned to classes, including, for example, face, clothes, body skin, or hair. The machine learning system can be implemented using a convolutional neural network that is configured to execute efficiently on computing devices having limited resources, such as mobile phones. The pixel mask can be used to more accurately display video effects interacting with a user or subject depicted in the image.

Abstract: Embodiments of the present disclosure provide a display method and apparatus based on augmented reality, a device, and a storage medium, the method includes receiving a first video; acquiring a video material by segmenting a target object from the first video; acquiring and displaying a real scene image, where the real scene image is acquired by an image collection apparatus; and displaying the video material at a target position of the real scene image in an augmented manner and playing the video material. Since the video material is acquired by receiving the first video and segmenting the target object from the first video, the video material may be set according to the needs of the user.

Abstract: A list information display method and apparatus, an electronic device, and a storage medium are provided, the method includes: displaying list information in response to an information display operation triggered by a user; obtaining a real scene shooting image; and loading a plurality of types of information related to the list information into the real scene shooting image and display the real scene shooting image. Due to the use of virtual enhanced display technology, while the list information is displayed in the real scene shooting image, the plurality of types of information related to the list information are also displayed. On one hand, the user can obtain more information related to the list information while obtaining the list information, which improves the efficiency of information acquisition; and on the other hand, the user can obtain information in the real scene shooting image, which improves the visual effect and interactive experience.