Abstract:
A method of playing advertisements according to exemplary embodiments includes collecting data of at least two viewers near a display, extracting relationship information of the at least two viewers based on the data, determining advertisements to play on the display according to the relationship information, and playing the determined advertisements on the display.
Abstract:
A processor-implemented method with image generation includes obtaining a first image, determining predicted texture information of a target image corresponding to the first image through a texture prediction model, based on the first image, determining predicted color information of the target image through a color prediction model, based on the first image, and generating the target image based on the first image, using the predicted texture information and the predicted color information, wherein a format of the target image is different from that of the first image.
Abstract:
A processor-implemented method with image processing includes obtaining point cloud data of a target scene, generating a feature map of the point cloud data by extracting a feature from the point cloud data, for each of a plurality of objects included in the target scene, generating a feature vector indicating the object in the target scene based on the feature map, and reconstructing a panorama of the target scene based on the feature vectors of the objects.
Abstract:
An apparatus and method for processing an image are disclosed. The method includes: segmenting both a first image and a second image and generating segmentation mask pairs, each segmentation mask pair having a segmentation mask of the first image and a segmentation mask of the second image; generating local homography matrices of the first image with respect to the second image, based on the segmentation mask pairs, the first image, and the second image; and generating a synthetic image obtained by aligning the first image with the second image, wherein the aligning is performed based on the local homography matrices, the segmentation mask pairs, the first image, and the second image.
Abstract:
A processor-implemented method includes obtaining an input image, predicting light source color information of a scene corresponding to the input image and a panoramic image corresponding to the input image using an image processing model, and generating a rendered image by rendering the input image based on either one or both of the light source color information and the panoramic image.
Abstract:
An apparatus and method with depth estimation are disclosed. The method includes calculating a first reliability of each of a plurality of time of flight (ToF) pixels of a ToF image; and generating, based on the first reliabilities, a depth map of a scene based on a left image and a right image and selectively based on the ToF image.
Abstract:
Disclosed is a method and device for processing data, and the method includes generating a target augmentation task sequence by processing the target data with a trained first model that performs inference on the target data to generate the target data augmentation task sequence, generate augmented target data by performing data augmentation on the target data according to the target augmentation task sequence, and obtaining a prediction result corresponding to the target data by inputting the augmented target data to a trained second model and performing a corresponding processing on the augmented target data by the trained second model.
Abstract:
A processor-implemented method with target tracking includes: generating a first target tracking result based on a search region of a current frame image; determining a scale feature of the first target tracking result; predicting a scale of a target in the search region based on the scale feature of the first target tracking result; and generating a second target tracking result by adjusting the first target tracking result based on a scale predicting result.
Abstract:
An electronic device and method with gaze estimating are disclosed. The method includes obtaining target information of an image, the image including an eye, obtaining a target feature map representing information on the eye in the image based on the target information, and estimating a gaze for the eye in the image based on the target feature map. The target information includes either attention information on the image, or a distance between pixels in the image, or both.
Abstract:
A method with object pose estimation includes: obtaining an instance segmentation image and a normalized object coordinate space (NOCS) map by processing an input single-frame image using a deep neural network (DNN); obtaining a two-dimensional and three-dimensional (2D-3D) mapping relationship based on the instance segmentation image and the NOCS map; and determining a pose of an object instance in the input single-frame image based on the 2D-3D mapping relationship.