Abstract: Embodiments of the present disclosure disclose an image processing method and apparatus, an image device, and a storage medium. The image processing method includes: obtaining an image; obtaining first rotation information of each of multiple nodes of a target; determining second rotation information of each child node with respect to a parent node in the multiple nodes of the target according to a hierarchical relationship among the nodes and multiple pieces of the first rotation information; and controlling movements of nodes in a controlled model corresponding to the multiple nodes based on multiple pieces of the second rotation information.

Abstract: Provided are an image processing method and device and an electronic device. The method may include: a first image and a second image are obtained; a facial key point of a target object in the first image is detected to obtain information of a first key point; a facial key point of a target object in the second image is detected to obtain information of a second key point; a conversion relationship is determined based on the information of the first key point and the information of the second key point; and faces of the target objects in the first image and the second image are fused based on the conversion relationship to obtain a third image.

Abstract: Embodiments of the present disclosure disclose a target detecting method and apparatus, a training method, an electronic device, and a medium. The target detecting method includes: separately extracting, by means of a neural network, characteristics of a template frame and a detection frame, where the template frame is a detection box image of a target object, and the template frame is smaller than the detection frame in image size; obtaining a classification weight and a regression weight of a local region detector based on the characteristic of the template frame; inputting the characteristic of the detection frame into the local region detector to obtain classification results and regression results of multiple alternative boxes output by the local region detector; and obtaining a detection box for the target object in the detection frame according to the classification results and regression results of the multiple alternative boxes output by the local region detector.

Abstract: A method and apparatus for positioning a description statement in an image includes: analyzing a to-be-analyzed description statement and a to-be-analyzed image to obtain a plurality of statement attention weights of the to-be-analyzed description statement and a plurality of image attention weights of the to-be-analyzed image; obtaining a plurality of first matching scores based on the plurality of statement attention weights and a subject feature, a location feature and a relationship feature of the to-be-analyzed image; obtaining a second matching score between the to-be-analyzed description statement and the to-be-analyzed image based on the plurality of first matching scores and the plurality of image attention weights; and determining a positioning result of the to-be-analyzed description statement in the to-be-analyzed image based on the second matching score.

Abstract: A first three-dimensional (3D) model of a target in a 3D space is acquired based on a first two-dimensional (2D) image including the target. A 3D morphing parameter is acquired. The first 3D model is transformed into a second 3D model based on the 3D morphing parameter. First 2D coordinates are acquired by mapping the first 3D model to a 2D space. Second 2D coordinates are acquired by mapping the second 3D model to the 2D space. A second 2D image including a morphed target is acquired by morphing the target in the first 2D image based on the first 2D coordinates and the second 2D coordinates.

Abstract: A method and apparatus for controlling a virtual object, a terminal, and a storage medium are disclosed. The method includes: acquiring a plurality of images of a user; determining, according to the plurality of images acquired, a gesture change parameter of a gesture change of the user; and controlling, according to the gesture change parameter, a virtual object corresponding to the user.

Abstract: The present disclosure discloses an image processing method and related device thereof. The method includes: acquiring an image to be processed; and performing a feature extraction process on the image to be processed using a target neural network so as to obtain target feature data of the image to be processed, wherein parameters of the target neural network are time average values of parameters of a first neural network which is obtained from training under supervision by a training image set and an average network, and parameters of the average network are time average values of parameters of a second neural network which is obtained from training under supervision by the training image set and the target neural network. A corresponding device is also disclosed. Feature data of image to be processed are obtained via the feature extraction process performed on the image to be processed.

Abstract: A convolution acceleration and computing processing method includes: reading data to be processed of a preset size in a task to be processed from an off-chip memory of an accelerator sequentially through a FIFO port, and storing the data to be processed into at least one input buffer of a first buffer in an on-chip memory of the accelerator; responsive to data to be processed being stored into an input buffer, reading input window data to be processed from the at least one input buffer sequentially, performing convolution on the input window data to be processed by using the convolution kernel data to obtain output window data and storing the output window data in the third buffer; and storing the output window data in the third buffer into the off-chip memory sequentially through the FIFO port.

Abstract: An Augmented Reality (AR) scene image processing method, an electronic device and a storage medium are provided. The method includes that: shooting pose data of an AR device is acquired; presentation special effect data of a virtual object corresponding to the shooting pose data in a reality scene is acquired based on the shooting pose data and position pose data of the virtual object in a three-dimensional scene model representing the reality scene; and an AR scene image is displayed through the AR device based on the presentation special effect information.

Abstract: A stereoscopic display device includes a case, a transparent display screen and one or more light sources. The case includes a chamber, one side of which is a front plate, the front plate is transparent, the transparent display screen is received inside the chamber and directly faces the front plate, the light sources are arranged inside the chamber and give off light towards the transparent display screen, and a picture displayed on the transparent display screen forms a reflection at the transparent display screen or at a bottom of the chamber.

Abstract: A method of detecting target object includes: extracting, through a neural network, a feature of a reference frame and a feature of a frame under detection; inputting each of at least two feature groups from at least two network layers of the neural network into a detector so as to obtain a corresponding detection result group output from the detector; wherein each feature group includes features of the reference frame and of the frame under detection, each detection result group includes a classification result and a regression result with respect to each of a plurality of candidate boxes for a feature group; and acquiring a bounding box for the target object in the frame under detection according to the at least two detection result groups.

Abstract: A method for image processing comprises: acquiring first, second, third, and fourth optical flow maps of t-th to (t?1)-th frame images, t-th to (t+1)-th frame images, (t+1)-th to t-th frame images, and (t+1)-th to (t+2)-th frame images, respectively, wherein t is an integer; determining first and second interpolation optical flow maps according to the first and second optical flow maps, and the third and fourth optical flow maps, respectively; determining a first interpolation frame image according to the first interpolation optical flow map and the t-th frame image, and a second interpolation frame image according to the second interpolation optical flow map and the (t+1)-th frame image; and fusing the first and second interpolation frame images to obtain an interpolation frame image to be interpolated between the t-th and (t+1)-th frame images. The embodiment of the present disclosure is capable of improving the accuracy of the obtained interpolation frame image.

Abstract: The present disclosure relates to an image processing method and apparatus, an electronic device, and a storage medium. The method includes: performing feature extraction on a to-be-processed image to obtain a first feature map of the to-be-processed image; performing target region prediction on the first feature map to determine a first region where a target is located in the first feature map; and performing key point detection on the first feature map according to the first region to determine target key point information of the to-be-processed image. According to embodiments of the present disclosure, quick and accurate target key point detection can be implemented.

Abstract: An image processing method includes: performing inspection on an image to be processed, and determining a contour line of a target object in the image to be processed and regions of the target object; determining, for a selected first region, first adjustment parameters of target pixel points in the first region according to set parameters; determining, for a second region adjacent to the first region, second adjustment parameters of reference pixel points in the second region; and adjusting the image to be processed according to the first and second adjustment parameters to determine an adjusted image.

Abstract: Methods and apparatuses for dynamically adding facial images into a database, electronic devices, media and programs include: comparing an obtained first facial image with pre-stored facial image information in an image database; and in response to a comparison result indicating that the first facial image has no matched pre-stored facial image information in the image database, determining whether to store at least one of the first facial image and feature information of the first facial image in the image database. Control of dynamically adding facial images into the database can therefore be achieved.

Abstract: A virtual avatar generation method includes: determining a target task associated with at least one target face property, where the at least one target face property is one of a plurality of predefined face properties respectively; performing, according to the target task, target face property analysis on a target image including at least a face to obtain a target face property feature associated with the target face property of the target image; determining a target virtual avatar template corresponding to the target face property feature according to predefined correspondence between face property features and virtual avatar templates; and generating a virtual avatar of the target image based on the target virtual avatar template.

Abstract: A method and for child state analysis, a vehicle, an electronic device, and a storage medium are provided. The method includes: performing face feature extraction on at least one image frame in an obtained video stream; classifying whether a person in the image is a child and at least one state of the person according to face features to obtain a first classification result of whether the person in the image is a child, and a second classification result of the at least one state of the person; outputting the first classification result and the second classification result; and/or outputting prompt information according to the first classification result and the second classification result.

Abstract: Provided are an image processing method and apparatus, an electronic device, and a storage medium. The method includes: identifying a first object to be rendered in a target image and a second object to which the first object belongs in the target image; generating a reference image including a mark based on the target image and the second object, the mark being used for recording a coverage area of the second object; determining an area to be rendered based on the reference image and the first object, the area to be rendered being located within the coverage area corresponding to the mark; and rendering the area by utilizing a target material to generate a rendering result. Through the process, the rendering range can be constrained when the first object is rendered based on the reference image including the mark generated by the second object to which the first object belongs, so that the reliability and authenticity of a rendering result are improved.

Abstract: Provided are a target object processing method and apparatus, and a storage medium. The method includes: inputting first data into a first processing module to obtain a predicted data annotation result; inputting the data annotation result into a second processing module, and performing scene-adaptive incremental learning according to the data annotation result to obtain a neural network adapted to a scene of second data; and processing a scene corresponding to a target object according to data including the target object and the neural network.

Abstract: The embodiments disclose a method and device for liveness detection and a computer-readable storage medium. The method includes that: a first image collected by a first image sensor of a binocular camera is acquired, and a second image collected by a second image sensor of the binocular camera is acquired: binocular matching processing is performed on the first image and the second image to obtain parallax information of the first image and the second image; and a Iiveness detection result is obtained according to the parallax information. By adopting the embodiments of the present disclosure, the accuracy of liveness detection can be improved.