Image transformation tasks such as cropping, text addition etc. are common across industries. Each industry has different business context and demands the image transformations be performed aligned to the business context. This disclosure relates to a system and method for an adaptive image transformation for a given context and maintaining aesthetic sense of the transformed image. Herein, the system is configurable and adaptive to any business context or domain. The system learns the context from available domain samples and creates an automated workflow of context-aware transformation tasks that maintains both the content and aesthetics demands of the context. Further, a saliency map is extracted for the identified RoI to append a text to the RoI based on the extracted saliency map, the calculated similarity metric for various content and aesthetic factors and various preferences of the user.

Embodiments of the present invention are directed to facilitating region of interest preservation. In accordance with some embodiments of the present invention, a region of interest preservation score using adaptive margins is determined. The region of interest preservation score indicates an extent to which at least one region of interest is preserved in a candidate image crop associated with an image. A region of interest positioning score is determined that indicates an extent to which a position of the at least one region of interest is preserved in the candidate image crop associated with the image. The region of interest preservation score and/or the preserving score are used to select a set of one or more candidate image crops as image crop suggestions.

A method of cropping an image containing an image of a human face includes detecting a region occupied by the image of the human face within the image, evaluating a plurality of candidate crops of the image, and selecting a crop of the image from the plurality of candidate crops of the image based on the results of the evaluation. The evaluating step includes applying a penalty to a candidate crop of the image in which the detected region occupied by the image of the human face is excluded or only partially included.

The present subject matter refers an image-processing method comprises receiving a first-image of an object captured by a range-imaging device at a first viewing location. The transforming the first-image into a second image of the object, said second image corresponding to an image captured based on range-imaging at a second viewing location with respect to the object. The gaps in the second-image are identified based on comparison with the first image, such that the identified gaps within the second image are complemented to result in a complemented second image.

An image processing method and apparatus, and a computer storage medium are provided. The method includes: obtaining a first image, recognizing a target object in the first image, acquiring a first target area of the target object, and acquiring a second target area associated with the first target area; and performing image deformation processing on the first target area and simultaneously performing image deformation processing on the second target area, to generate a second image.

A method and an apparatus for a complete size adaptation of an object to be displayed are provided. The method includes obtaining elements and description information of the elements included in an object to be displayed, the description information of the elements including information of parent-child relationships among the elements and rules for adaptation into display areas of different sizes based on the parent-child relationships; determining sizes and positions of the elements that are included in the object to displayed and are adapted to a current display area based on the elements and the description information of the elements that are obtained and size information of the current display area; and displaying the elements included in the object to be displayed in the current display area using the sizes and the positions that are determined.

A method and apparatus for processing an image interaction are provided. The apparatus extracts, using an encoder, an input feature from an input image, converts the input feature to a second feature based on an interaction for an application to the input image, and generates, using a decoder, a result image from the second feature.

An apparatus and method for geometrically correcting a distorted input frame and generating an undistorted output frame. The apparatus includes an external memory block that stores the input frame, a counter block to compute output coordinates of the output frame for a region based on a block size of the region, a back mapping block to generate input coordinates corresponding to each of the output coordinates, a bounding module to compute input blocks corresponding to each of the input coordinates, a buffer module to fetch data corresponding to each of the input blocks, an interpolation module to interpolate data from the buffer module and a display module that receives the interpolated data for each of the regions and stitch an output image. The method includes determining the size of the output block based on a magnification data.

A style of a digital image is transferred to another digital image of arbitrary resolution. A high-resolution (HR) content image is segmented into several low-resolution (LR) patches. The resolution of a style image is matched to have the same resolution as the LR content image patches. Style transfer is then performed on a patch-by-patch basis using, for example, a pair of feature transformswhitening and coloring. The patch-by-patch style transfer process is then repeated at several increasing resolutions, or scale levels, of both the content and style images. The results of the style transfer at each scale level are incorporated into successive scale levels up to and including the original HR scale. As a result, style transfer can be performed with images having arbitrary resolutions to produce visually pleasing results with good spatial consistency.

In accordance with implementations of the subject matter described herein, there is proposed a solution of visual stylization of stereoscopic images. In the solution, a first feature map for a first source image and a second feature map for a second source image are extracted. The first and second source images correspond to first and second views of a stereoscopic image, respectively. A first unidirectional disparity from the first source image to the second source image is determined based on the first and second source images. First and second target images having a specified visual style are generated by processing the first and second feature maps based on the first unidirectional disparity. Through the solution, a disparity between two source images of a stereoscopic image are taken into account when performing the visual style transfer, thereby maintaining a stereoscopic effect in the stereoscopic image consisting of the target images.