Abstract: An image processing method, performed by a computer device, includes: obtaining an input image to be processed; performing face detection on the input image to obtain an input face image to be processed including at least one defect element relating to a skin element; and inputting the input face image into an image processing model to obtain a target face image corresponding to the input face image without a first defect element amongst the at least one defect element, wherein a training sample of the image processing model includes a first face image with a first face distortion degree less than a preset threshold and that is annotated with the first defect element.

Abstract: A face image processing method and apparatus, a face image display method and apparatus, and a device are provided, belonging to the technical field of image processing. The method includes: acquiring a first face image of a person; invoking an age change model to predict a texture difference map of the first face image at a specified age, the texture difference map being used for reflecting a texture difference between a face texture in the first face image and a face texture of a second face image of the person at the specified age; and performing image processing on the first face image based on the texture difference map to obtain the second face image.

Abstract: A display substrate and a display device. The display substrate includes a base substrate, a plurality of sub-pixels, and a partition structure. The plurality of sub-pixels are located on the base substrate; each sub-pixel includes a light-emitting element; the light-emitting element includes a light-emitting functional layer and a first electrode and a second electrode located on either side of the light-emitting functional layer; the second electrode is located between the light-emitting functional layer and the base substrate; and the light-emitting functional layer includes a charge generation layer. The partition structure is located on the base substrate and between adjacent sub-pixels; and the charge generation layer in the light-emitting functional layer is disconnected at the positions where the partition structure is located.

Abstract: The present disclosure provides a pixel circuit, a driving method and a display device. The pixel circuit includes a light-emitting element, a driving circuit, a first light-emitting control circuit, a first control circuit, a first initialization circuit and a second light-emitting control circuit. The first control circuit is configured to control to connect the first node and the control node under the control of a first scan signal; the first initialization circuit is configured to write a first initial voltage into the control node under the control of a second light-emitting control signal; the first light-emitting control circuit is configured to control to connect the power supply voltage terminal and the second node under the control of the second light-emitting control signal.

Abstract: The present disclosure provides a display substrate, which includes a base substrate (101), a first power supply line (321a), a plurality of first signal leads (341), a plurality of test connection traces (342), at least one first connection line (381), and a plurality of test signal access pins (361). At least one first signal lead (341) is electrically connected to at least one test signal access pin (361) through at least one test connection trace (342). The first connection line (381) is located at a side of the plurality of test connection traces (342) and the plurality of test signal access pins (361) close to an edge of the peripheral area in a first direction (X). The first connection line (381) at least extends along a second direction (Y) and is electrically connected to the first power supply line (321a).

Abstract: A face detection method includes: acquiring a target image; invoking a face detection network, and processing the target image by using a feature extraction structure of the face detection network, to obtain original feature maps corresponding to the target image; the original feature maps having different resolutions; processing the original feature maps by using a feature enhancement structure of the face detection network, to obtain an enhanced feature map corresponding to each original feature map; the feature enhancement structure being obtained by searching a search space, and the search space used for searching the feature enhancement structure being determined based on a detection objective of the face detection network and a processing object of the feature enhancement structure; and processing the enhanced feature map by using a detection structure of the face detection network, to obtain a face detection result of the target image.

Abstract: A fabrication method for a steel thin-walled tailor-welded part and a hot-stamped part prepared by using the tailored welded part, the method comprising: using steel plates (10, 10, 20) to be welded which have an aluminum or aluminum alloy coating (12, 12?, 22, 22?) is used; by means of adjusting the composition of a shielding gas (50) and the composition of a welding wire (30) during a welding process, in combination with the control of the welding speed and wire-feeding speed, controlling the content of free aluminum in a weld seam to be 0.1 to 4.0 wt. %, which prevents the production of iron-aluminum intermetallic compounds in the weld seam during a tailor welding process while ensuring that an appropriate amount of ferrite which is distributed in a dispersed manner is produced in the weld seam. The weld seam structure of the obtained tailor-welded part is +1 to 15 vol. % martensite, +0 to 5 vol. % ferrite which is distributed in a dispersed manner, and the remainder is austenite.

Abstract: The present invention provides an asphaltene dispersion stabilizer and a preparation method therefor, and relates to the technical field of oilfield additives. The asphaltene dispersion stabilizer is prepared by the following method: taking iminodisuccinic acid or salt thereof, and performing Michael addition reaction on the iminodisuccinic acid or the salt thereof and unsaturated sulfonate to prepare a first intermediate; taking the first intermediate, and performing amidation reaction on the first intermediate and a first monomer under the action of a catalyst to obtain a second intermediate; and preparing a dendrimer by taking the second intermediate as a core and taking a second monomer and a third monomer as raw materials, wherein the dendrimer is the asphaltene dispersion stabilizer, and the generation number of the dendrimer is 0.5 generations, 1.5 generations or 2.5 generations. The asphaltene dispersion stabilizer of the present invention has a good dispersion stabilization effect on asphaltene.

Abstract: An array substrate is provided. The array substrate includes a base substrate; an auxiliary structure in an inter-subpixel region and on the base substrate; and a cathode layer on a side of the auxiliary structure away from the base substrate. The auxiliary structure includes a plurality of groups of auxiliary blocks, a respective group of the plurality of groups of auxiliary blocks including one or more auxiliary blocks protruding away from the base substrate. The plurality of groups of auxiliary blocks are configured to enhance adhesion between an organic layer and an adjacent layer and reduce or eliminate interlayer peeling therebetween.

Abstract: Provided are a display substrate, a manufacturing method thereof and a display device. In the display substrate, the second separation part has a protruding part, the protruding part protrudes relative to a side of the first separation part close to the second separation part, at least one sub-functional layer of the light-emitting functional layer is disconnected at the protruding part, a material of the first separation part includes an organic material, a material of the second separation part includes an organic material, and along a direction from the first electrode to the second electrode, an orthographic projection of the separation structure on the base substrate gradually decreases and then gradually increases.

Abstract: A display panel has a first display region, at least one second display region and a third display region. The display panel includes a substrate, an anode layer and a pixel definition layer. The anode layer is disposed on the substrate and includes a plurality of anodes. The pixel definition layer is disposed on a side of the anode layer away from the substrate. The pixel definition layer is provided with a plurality of openings therein, an opening corresponds to an anode, and the opening exposes at least a portion of the anode corresponding thereto. The first display region, the at least one second display region and the third display region are each provided with openings of the plurality of openings, and aperture ratios of the first display region, the at least one second display region and the third display region sequentially decrease.

Abstract: An image generation method, performed by an electronic device includes obtaining an original face image frame, audio driving information, and emotion driving information, performing spatial feature extraction on the original face image frame to obtain an original face spatial feature corresponding to the original face image frame; performing feature interaction processing on the audio driving information and the emotion driving information to obtain a face local pose feature of the to-be-adjusted object issuing the voice content with the target emotion; and performing, based on the original face spatial feature and the face local pose feature, face reconstruction processing on the to-be-adjusted object to generate a target face image frame.

Abstract: A video data processing method is provided to a server. The method includes: obtaining a video sequence associated with a video source and obtaining a video quality standard parameter associated with the video sequence; determining a video feature according to video quality standard parameter; predicting an encoding bit rate according to the video quality standard parameter and the video feature; and encoding the video sequence according to the encoding bit rate to obtain an encoded video sequence associated with the video source.

Abstract: An image processing method including obtaining a fake template sample group comprising a first source image, a real labeled image, and a fake template image, inputting the fake template image into an identity swapping model to obtain a first identity swapping image of the fake template image, obtaining a fake labeled sample group comprising a second source image, a real template image, and a fake labeled image, the fake labeled image being based on identity swapping processing of the real template image, inputting the real template image into the identity swapping model to obtain a second identity swapping image of the real template image, and training the identity swapping model based on the fake template sample group, the first identity swapping image, the fake labeled sample group, and the second identity swapping image to generate a trained identity swapping model.

Abstract: In an image optimization method, an image generation network, a to-be-optimized image, and a plurality of preset image features are obtained. A target feature is selected from the plurality of preset image features based on (i) the target feature and the to-be-optimized image and (ii) a preset similarity condition. The target feature and an initial offset parameter are input to the image generation network. The initial offset parameter is adjusted according to a difference between an output of the image generation network and the to-be-optimized image, to obtain a target offset parameter. The target feature and the target offset parameter are input to the image generation network, to generate an optimized image. Apparatus and non-transitory computer-readable storage medium counterpart embodiments are also contemplated.

Abstract: This application discloses a method for generating an image processing model performed by a computer device. The method includes: performing training by using a first source image sample, a first template image sample, and a first standard synthesized image, to obtain a first parameter adjustment model, and combining the first parameter adjustment model and a first resolution update layer into a first update model; adjusting the first update model into a second parameter adjustment model using a second source image sample and a second template image sample and a second standard synthesized image; combining the second parameter adjustment model and a second resolution update layer into a second update model; and adjusting the second update model into a target image fusion model using a third source image sample, a third template image sample and a third standard synthesized image.

Abstract: A target tracking method is provided for a computer device. The method includes determining a target candidate region of a current image frame; capturing a target candidate image matching the target candidate region from the current image frame; determining a target region of the current image frame according to an image feature of the target candidate image; determining motion prediction data of a next image frame relative to the current image frame by using a motion prediction model and according to the image feature of the target candidate image; and determining a target candidate region of the next image frame according to the target region and the motion prediction data.

Abstract: An action recognition method includes: obtaining original feature submaps of each of temporal frames on a plurality of convolutional channels by using a multi-channel convolutional layer; calculating, by using each of the temporal frames as a target temporal frame, motion information weights of the target temporal frame on the convolutional channels according to original feature submaps of the target temporal frame and original feature submaps of a next temporal frame, and obtaining motion information feature maps of the target temporal frame on the convolutional channels according to the motion information weights; performing temporal convolution on the motion information feature maps of the target temporal frame to obtain temporal motion feature maps of the target temporal frame; and recognizing an action type of a moving object in image data of the target temporal frame according to the temporal motion feature maps of the target temporal frame on the convolutional channels.

Abstract: This application relates to a method and an apparatus for detecting facial key points, a computer device, and a storage medium including: acquiring a to-be-detected face image from a current frame; determining partial images in the to-be-detected face image, each partial image including one or more facial key points; determining, within each of the partial images, candidate points of the one or more facial key points corresponding to the partial image, respectively; and jointly constraining the candidate points in the partial images to determine a set of facial key points from the candidate points for the to-be-detected face image. For the partial images in the entire to-be-detected face image, the candidate points of the facial key points corresponding to the partial images are respectively determined. Therefore, a calculation amount may be reduced, and the efficiency of determining the candidate points of the facial key points is improved.

Abstract: A face liveness detection method is performed by an electronic device. The method includes: obtaining an initial face image of an object and a face image set of the object captured at N different illumination directions; obtaining N difference images according to the initial face image and the N face images in the face image set; generating a normal map and an albedo map according to the N difference images and the N illumination directions; and determining a face liveness detection result according to the N difference images, the normal map, and the albedo map, the face liveness detection result indicating whether the object has a live face or not. In this application, three-dimensional (3D) geometric information and surface material information of a face image are considered, thereby recognizing the authenticity of the face image, and effectively resisting different face liveness attack manners.