Tencent Technology (shenzhen) Company Limited

Sz Dji Technology Co., Ltd.

Sz Dji Osmo Technology Co., Ltd.

Tencent Technology Company Limited

Linchao Bao

Xiangkai Lin

Yan Zhang

Zisheng Cao

Yonggen Ling

Mingyu Wang

Liang Qiao

Pan Hu

Fengming Zhu

Chenglin Mao

Sheng Wang

Xing Ji

Yu Zuo

Zhantu Zhu

Zeyu Yang

Peng Liu

Yibing Song

Shiyin Kang

Deyi Tuo

Kuongchi Lei

Wei Zhang

Cong Zhao

You Zhou

Yuan Gao

Paul Pan

Xiaolong Zhu

Ye Tao

Lifu Yu

Xuyang Feng

Zhuo Guo

Zihan Chen

Jiaqi Yan

Guanhua Su

Wenhan Luo

Yitong Wang

Weidong Chen

Yajing Chen

Mu Hu

Di Kang

Sirui Gao

Wenpan Li

Xuefei Zhe

Embodiments of this application disclose a method and an apparatus for generating a three-dimensional face model. The method includes obtaining a plurality of target face images and a plurality of depth images corresponding to the plurality of target face images, the plurality of target face images comprising a same face; obtaining, according to an image type of each target face image, a regional face image that is in each target face image and that corresponds to the image type of each target face image, the image type comprising a front face type, a left face type, a right face type, or a head-up type; obtaining a regional depth image in a corresponding depth image according to the regional face image; and performing image fusion based on the plurality of obtained regional face images and the plurality of obtained regional depth images, to generate a three-dimensional face model.

Method and apparatus for generating three-dimensional face model, computer device, and storage medium

This application discloses a three-dimensional human pose estimation method performed by a computer device. An initialization pose estimation result of a single video frame in a video frame sequence of n views is extracted based on a neural network model. Single-frame and single-view human pose estimation is performed on the initialization pose estimation result for each video frame, to obtain n single-view pose estimation sequences respectively corresponding to the n views. Single-frame and multi-view human pose estimation is performed according to single-view pose estimation results with the same timestamp in the n single-view pose estimation sequences, to obtain a multi-view pose estimation sequence. Multi-frame and multi-view human pose estimation is performed on a multi-view pose estimation result in the multi-view pose estimation sequence, to obtain a multi-view and multi-frame pose estimation result. Therefore, accuracy of human pose estimation is improved.

Three-dimensional human pose estimation method and related apparatus

This application discloses an artificial intelligence (AI) based animation character drive method. A first expression base of a first animation character corresponding to a speaker is determined by acquiring media data including a facial expression change when the speaker says a speech, and the first expression base may reflect different expressions of the first animation character. After target text information is obtained, an acoustic feature and a target expression parameter corresponding to the target text information are determined according to the target text information, the foregoing acquired media data, and the first expression base. A second animation character having a second expression base may be driven according to the acoustic feature and the target expression parameter, so that the second animation character may simulate the speaker's sound and facial expression when saying the target text information, thereby improving experience of interaction between the user and the animation character.

Artificial intelligence-based animation character drive method and related apparatus

An image processing method and apparatus, a computer-readable medium, and an electronic device are provided. The image processing method includes: respectively projecting, according to a plurality of view angle parameters corresponding to a plurality of view angles, a face model of a target object onto a plurality of face images of the target object acquired from the plurality of view angles, to determine correspondences between regions on the face model and regions on the face image; respectively extracting, based on the correspondences and a target region in the face model that need to generate a texture image, images corresponding to the target region from the plurality of face images; and fusing the images that correspond to the target region and that are respectively extracted from the plurality of face images, to generate the texture image.

Image processing method and apparatus, computer-readable medium, and electronic device

Embodiments of this application disclose an artificial intelligence-based (AI-based) animation character control method. When one animation character has a corresponding face customization base, and one animation character has no corresponding face customization base, the animation character having the face customization base may be used as a driving character, and the animation character having no face customization base may be used as a driven character. The method may include: obtaining an expression base corresponding to the driving character and an expression base corresponding to the driven character; determining a mapping relationship between expression parameters according to the expression base corresponding to the driving character and the expression base corresponding to the driven character; and driving the driven character according to the mapping relationship by using the known expression parameter of the driving character and the foregoing mapping relationship, so that the driven character is driven to make an actual expression identified by the known expression parameter. Therefore, a new animation character may be directly driven by using a known expression parameter of another animation character without performing processing to obtain a face customization base corresponding to the new animation character, thereby increasing the speed of launching the new animation character.

Artificial intelligence-based animation character control and drive method and apparatus

A three-dimensional face model generation method is provided. The method includes: obtaining an inputted three-dimensional face mesh of a target object; aligning the three-dimensional face mesh with a first three-dimensional face model of a standard object according to face keypoints; performing fitting on the three-dimensional face mesh and a local area of the first three-dimensional face model, to obtain a second three-dimensional face model after local fitting; and performing fitting on the three-dimensional face mesh and a global area of the second three-dimensional face model, to obtain a three-dimensional face model of the target object after global fitting.

Three-dimensional face model generation method and apparatus, device, and medium

Embodiments of this application disclose a method for displaying a virtual character in a plurality of real-world images captured by a camera is performed at an electronic device. The method includes: capturing an initial real-world image using the camera; simulating a display of the virtual character in the initial real-world image; capturing a subsequent real-world image using the camera after a movement of the camera; determining position and pose updates of the camera associated with the movement of the camera from tracking one or more feature points in the initial real-world image and the subsequent real-world image; and adjusting the display of the virtual character in the subsequent real-world image in accordance with the position and pose updates of the camera associated with the movement of the camera.

Position and pose determining method, apparatus, smart device, and storage medium

A method for an image capturing device includes: acquiring a first image of a target object; extracting coordinate information of a first 2D key point corresponding to the target object; acquiring a second image of the target object; acquiring coordinate information of a second 2D key point in the second image according to the coordinate information of the first 2D key point, the first 2D key point and the second 2D key point being the same key point in the target object; acquiring coordinate information of a 3D key point corresponding to the target object, the 3D key point being a key point obtained after a triangulation operation; and determining camera posture information of the second image according to the coordinate information of the first 2D key point, the coordinate information of the second 2D key point, the coordinate information of the 3D key point, and a 3D-2D projection.

Method for augmented reality display, method for determining pose information, and apparatuses

This application provides a three-dimensional (3D) expression base generation method performed by a computer device. The method includes: obtaining image pairs of a target object in n types of head postures, each image pair including a color feature image and a depth image in a head posture; constructing a 3D human face model of the target object according to then image pairs; and generating a set of expression bases of the target object according to the 3D human face model of the target object. According to this application, based on a reconstructed 3D human face model, a set of expression bases of a target object is further generated, so that more diversified product functions may be expanded based on the set of expression bases.

Three-dimensional expression base generation method and apparatus, speech interaction method and apparatus, and medium

A computer application method for generating a three-dimensional (3D) face model is provided, performed by a face model generation model running on a computer device, the method including: obtaining a two-dimensional (2D) face image as input to the face model generation model; extracting global features and local features of the 2D face image; obtaining a 3D face model parameter based on the global features and the local features; and outputting a 3D face model corresponding to the 2D face image based on the 3D face model parameter.

Computer application method and apparatus for generating three-dimensional face model, computer device, and storage medium

This application disclose an artificial intelligence (AI) based animation character drive method. A first expression base of a first animation character corresponding to a speaker is determined by acquiring media data including a facial expression change when the speaker says a speech, and the first expression base may reflect different expressions of the first animation character. After target text information is obtained, an acoustic feature and a target expression parameter corresponding to the target text information are determined according to the target text information, the foregoing acquired media data, and the first expression base. A second animation character having a second expression base may be driven according to the acoustic feature and the target expression parameter, so that the second animation character may simulate the speaker's sound and facial expression when saying the target text information, thereby improving experience of interaction between the user and the animation character.

Embodiments of this application disclose a method for determining camera pose information of a camera of a mobile terminal. The method includes: obtaining a first image, a second image, and a template image, the first image being a previous frame of image of the second image, the first image and the second image being images including a respective instance of the template image captured by the mobile terminal using the camera at a corresponding spatial position; determining a first homography between the template image and the second image; determining a second homography between the first image and the second image; and performing complementary filtering processing on the first homography and the second homography, to obtain camera pose information of the camera, wherein the camera pose information of the camera represents a spatial position of the mobile terminal when the mobile terminal captures the second image using the camera.

Method, device and storage medium for determining camera posture information

This application discloses a repositioning method and apparatus in a camera pose tracking process, a device, and a storage medium, belonging to the field of augmented reality (AR). The method includes: obtaining a current image acquired after an ianchor image in a plurality of anchor images; obtaining an initial feature point and an initial pose parameter in the first anchor image in the plurality of anchor images in a case that the current image satisfies a repositioning condition; performing feature point tracking on the current image relative to the first anchor image, to obtain a plurality of matching feature point pairs; filtering the plurality of matching feature point pairs according to a constraint condition, to obtain a filtered matching feature point pair; calculating a pose change amount of a camera from the initial pose parameter to a target pose parameter according to the filtered matching feature point pair; and performing repositioning according to the initial pose parameter and the pose change amount to obtain the target pose parameter of the camera.

Relocalization method and apparatus in camera pose tracking process, device, and storage medium

This application provides a method for configuring parameters of a three-dimensional face model. The method includes: obtaining a reference face image; identifying a key facial point on the reference face image to obtain key point coordinates as reference coordinates; and determining a recommended parameter set in a face parameter value space according to the reference coordinates. The first projected coordinates are projected coordinates of the key facial point obtained by projecting a three-dimensional face model corresponding to the recommended parameter set onto a coordinate system. The proximity of the first projected coordinates to the reference coordinates meets a preset condition.

Parameter configuration method, apparatus, and device for three-dimensional face model, and storage medium

A system for supporting imaging includes an imaging device configured to capture a plurality of images for a substantially same scene using respective imaging configurations, a stabilization device configured to stabilize the imaging device on a mobile platform during the capturing of the plurality of images, and a controller communicating with at least one of the imaging device or the stabilization device and configured to control an operation of the mobile platform.

System, method, and mobile platform for supporting bracketing imaging

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Shenzhen, China

Linchao Bao