Snap Inc.

Bytedance Inc.

Beijing Bytedance Network Technology Co., Ltd.

Lemon Inc.

Guohui Wang

Jianchao Yang

Samuel Edward Hare

Fedir Poliakov

Linjie Yang

Sumant Milind Hanumante

Xuehan Xiong

Linjie Luo

Zhili Chen

Xiao Yang

Shah Tanmay Anilkumar

Jing Liu

Ning Xu

Tony Mathew

Yuncheng Li

William Brendel

Jingcong Zhang

Lidiia Bogdanovych

Fenglei Tian

Yunzhu Li

Xuchen Song

Xiaochen Lian

Haoze Li

Nan Hu

Kun Duan

Chongyang Ma

Zihao Chen

Yiheng Zhu

Ray McClure

Haiying Cheng

Shihkuang Chu

Liyou Xu

Anda Li

Yuanlong Chen

Weikai Li

Beixin Hu

A positioning model optimization method, an image-based positioning method and positioning device, and a computer-readable storage medium are provided. The positioning model optimization method includes: inputting a positioning model for a scene, the positioning model including a three-dimensional (3D) point cloud and a plurality of descriptors corresponding to each 3D point in the 3D point cloud; determining, for each 3D point in the 3D point cloud, a plurality of neighboring points of the 3D point, and if a distance relationship between each of the plurality of neighboring points and the 3D point is smaller than a predetermined threshold, outputting the 3D point and the plurality of descriptors corresponding to the 3D point to an optimized positioning model for the scene; and outputting the optimized positioning model for the scene.

Positioning model optimization method, positioning method, positioning device, and storage medium

A positioning model optimization method, a positioning method, and a positioning device are provided. The positioning model optimization method includes: inputting a positioning model for a scene, the positioning model including a three-dimensional (3D) point cloud and a plurality of descriptors corresponding to each 3D point in the 3D point cloud; calculating a significance of each 3D point in the 3D point cloud, and if the significance is greater than a predetermined threshold, outputting the 3D point and the plurality of descriptors corresponding to the 3D point to an optimized positioning model for the scene; and outputting the optimized positioning model for the scene.

Positioning model optimization method, positioning method, and positioning device

An animation processing method and apparatus, an electronic device and a storage medium, applied to a shader, the method including: acquiring an animation sample of a model unit; acquiring an external interaction parameter of an augmented reality model, where the augmented reality model includes a plurality of model units; and outputting the augmented reality model, and driving the animation sample of the model unit in the output augmented reality model according to the external interaction parameter. The animation sample of the model unit can be driven according to the external interaction parameter, so that animation of the model can be adjusted according to user operation, thereby improving usability.

Animation processing method and apparatus, electronic device and storage medium

Among other things, embodiments of the present disclosure improve the functionality of computer software and systems by facilitating the automatic performance optimization of a software application based on the particular platform upon which the application runs. In some embodiments, the system can automatically choose a set of parameters or methods at run-time from a design space with pre-selected optimization methods and parameters (e.g., algorithms, software libraries, and/or hardware accelerators) for a specific task.

Automatic software performance optimization

An image effect implementing method is described herein that includes: acquiring a first image, recognizing a set object in the first image, and acquiring an augmented reality model corresponding to the set object; superimposing, according to coordinate information of pixels of the set object, the augmented reality model onto the first image to obtain a second image; and upon detection of a preset deformation event, controlling, according to a set deformation policy, at least one sub-model of the augmented reality model in the second image to deform, and displaying the deformed second image.

Image effect implementing method and apparatus, electronic device and storage medium

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.

Ranking list information display method and apparatus, and electronic device and storage medium

Remote distribution of multiple neural network models to various client devices over a network can be implemented by identifying a native neural network and remotely converting the native neural network to a target neural network based on a given client device operating environment. The native neural network can be configured for execution using efficient parameters, and the target neural network can use less efficient but more precise parameters.

Remote distribution of neural networks

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.

Generating an image mask using machine learning

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.

Real-time tracking-compensated image effects

Systems and methods are provided for initiating transfer of image data corresponding to at least one predetermined level of an image pyramid comprising higher resolution to a graphic processing unit (GPU) of the computing device, calculating, by the central processing unit (CPU) of the computing device, optical flow of at least one predetermined coarse level of the image pyramid, transferring, by the CPU of the computing device, the calculated optical flow of the at least one predetermined coarse level of the image pyramid to the GPU, calculating, by the GPU of the computing device, the optical flow of the at least one predetermined level of the image pyramid comprising higher resolution, and outputting, by the GPU of the computing device, the optical flow of the image data.

Efficient parallel optical flow algorithm and GPU implementation

An image processing method and apparatus for augmented reality, an electronic device and a storage medium, including: acquiring a target image in response to an image acquiring instruction triggered by a user, where the target image includes a target object; acquiring an augmented reality model of the target object, and outputting the augmented reality model in combination with the target object; acquiring target audio data selected by the user, and determining an audio feature with temporal regularity according to the target audio data; and driving the augmented reality model according to the audio feature and a playing progress of the target audio data when outputting the target audio data.

Image processing method and apparatus for augmented reality, electronic device, and storage medium

A machine learning system can generate an image mask (e.g., a pixel mask) comprising pixel assignments for pixels. The pixels can he 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.

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Los Angeles, CA, United States of America

Guohui Wang