A system for removing a noise artifact from an image of a document extracts a first set of features from the image, where the first set of features represents items on the image. The system identifies noise artifact features from the first set of features representing pixel values of the noise artifact. The system generates a second set of features by removing the noise artifact features from the first set of features. The system generates a test clean image of the document based on the second set of features as an input. The system determines whether a portion of the test clean image that previously displayed the noise artifact corresponds to a counterpart portion of the training clean image. If it is determined that the portion of the test clean image corresponds to the counterpart portion of the training clean image, the system outputs the test clean image.

An image processing device replaces pixel values received from an imaging device that includes multiple types of pixels being arranged in a first pixel arrangement to detect different wavelength ranges of light, with pixel values of pixels in a second pixel arrangement different from the first pixel arrangement, by determining whether there is an edge indicating a direction along which pixels having a smaller change in pixel values are aligned that are positioned around a target pixel to be interpolated, and have a same color as the target pixel after replacement; and interpolating, if an edge is determined, a pixel value of the target pixel using the pixel values of the pixels along the direction of the edge, or if no edge, the pixel value of the target pixel using pixel values of pixels along a direction of another edge detected based on brightness around the target pixel.

A method and an apparatus for generating a virtual viewpoint image by obtaining at least one input viewpoint image and warping pixels of the at least one input viewpoint image to a virtual viewpoint image coordinate system; mapping a patch to a first pixel of a plurality of pixels warped to the virtual viewpoint image coordinate system when a difference between a first depth value of the first pixel and a second depth value of a second pixel adjacent to the first pixel is less than or equal to a predetermined threshold and mapping no patch to the first pixel when the difference is greater than the predetermined threshold; and generating the virtual viewpoint image by blending the plurality of pixels and/or the patch are provided.

A system and method for processing an input video while maintaining temporal consistency across video frames is provided. The method includes converting the input video from a first frame rate to a second frame rate, wherein the second frame rate is a faster frame rate than the first frame rate; generating processed frames of the input video at the second frame rate; and aggregating the processed frames using temporal sliding window aggregation to yield a processed output video at a third frame rate.

An inpainting method includes retrieving image information at an electronic device, where the image information identifies an area within an image. The method also includes retrieving, using the electronic device, semantic information including a plurality of semantic classes and a semantic class distribution for each semantic class of the plurality of semantic classes. The method further includes generating semantic codes associated with different portions of the image based on the image information and the semantic information. In addition, the method includes constructing the area within the image by generating image content based on the semantic information.

Provided are a beauty processing method and apparatus. The method includes: obtaining an original face image, and extracting original parameter information corresponding to a site feature of a to-be-beautified site; determining, based on the original parameter information, a site beauty parameter corresponding to the to-be-beautified site; and processing the to-be-beautified site based on the site beauty parameter to generate a target face image. Thus, the personalized beauty parameters can be generated to meet the user's personalized beauty needs, improving the accuracy of the beauty parameter and enhancing the beauty effect.

Embodiments of the present disclosure relate to the field of image processing technologies and disclose an image processing method and apparatus, an electronic device, and a computer-readable storage medium. The image processing method includes: when an obtained first image includes a human face, performing a first transformation process on the first image to obtain a second image; determining, based on a first target face key point of the human face in the first image, a target position, in the first image, of a second target face key point of the human face in the second image; performing a first movement process on the second image based on the target position; and generating a target image based on the first image and the second image processed through the first movement process, and displaying the target image.

The present disclosure relates to a video transmission method, an electronic device and a computer readable medium. The method is applied to a first application installed in a first terminal, where the first terminal is further installed with a second application. The method includes: acquiring a current video frame; performing special effect processing on the current video frame according to a received special effect setting instruction, and generating a target video frame; and sending the target video frame to the second application. Thus, the first application can be matched with any second application that needs to use a special effect processing function, and the second application can be enabled to obtain a special effect-processed video on the premise that the second application does not need to be redeveloped.

The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately, efficiently, and flexibly restoring degraded digital images utilizing a deep learning framework for repairing local defects, correcting global imperfections, and/or enhancing depicted faces. In particular, the disclosed systems can utilize a defect detection neural network to generate a segmentation map indicating locations of local defects within a digital image. In addition, the disclosed systems can utilize an inpainting algorithm to determine pixels for inpainting the local defects to reduce their appearance. In some embodiments, the disclosed systems utilize a global correction neural network to determine and repair global imperfections. Further, the disclosed systems can enhance one or more faces depicted within a digital image utilizing a face enhancement neural network as well.

Methods for improving and modifying a High Dynamic Range (HDR) scene, captured as a series of images of the scene with different exposure levels and the scene through classification-based image merging, tuning, correction, and replacement. The approach employs mixing images to improve the selection and display of both shadowed and highlighted details. The increased efficiency resulting from improvements in computational resource utilization of image processing hardware can, from the implementation of the improved computational methods herein, significantly reduce the time required to generate and display a tone-mapped HDR image, a gamma-corrected HDR image, and/or a segmented and replaced HDR image.