Provided is a method of adaptively performing artificial intelligence (AI) downscaling on an image during a video telephone call of a user terminal. The method includes obtaining, from an opposite user terminal, AI upscaling support information of the opposite user terminal that is a target of a video telephone call, determining whether the user terminal is to perform AI downscaling on an original image, based on the AI upscaling support information, based on determining that the user terminal is to perform AI downscaling on the original image, obtaining a first image by AI downscaling the original image using a downscaling deep neural network (DNN), generating image data by performing first encoding on the first image, and transmitting AI data including information related to the AI downscaling and the image data.

The embodiments are an image processing method and apparatus, an aerial camera and a storage medium. The method includes: receiving an image mode switching instruction, wherein the image mode switching instruction is configured to indicate to switch a current image mode into a target image mode, and the image mode switching instruction carries the target image mode; and processing a collected image according to the target image mode. Therefore, the image can be flexibly processed based on the target image mode in the image mode switching instruction, such that the image display requirements in different scenarios are met.

An image rendering method, device, and system, a storage medium, and an image display method are provided. The image rendering method includes: acquiring an image to be displayed; according to a gaze point of human eyes on a display screen, obtaining a gaze point position on the image to be displayed; determining, according to the gaze point position, a first sampling area and a second sampling area of the image to be displayed; performing first resolution sampling on the first sampling area to obtain a first display area; performing second resolution sampling on the image to be displayed to obtain a second display area corresponding to the second sampling area, a resolution of the second sampling area being greater than that of the second display area; and splicing the first display area and the second display area to obtain an output image to be transmitted to the virtual reality device.

Aspects of the subject disclosure may include, for example, obtaining image content over a communication network, determining a predicted viewpoint of a user associated with the image content, and adjusting the image content to equirectangular image content according to the predicted viewpoint. Further aspects can include downscaling the equirectangular image content according to a display capability of a mobile device resulting in a downscaled equirectangular image content, cropping the downscaled equirectangular image content resulting in a cropped equirectangular image content, and providing, over the communication network, the cropped equirectangular image content to the mobile device. Other embodiments are disclosed.

A display apparatus includes a display, a communicator configured to communicate with a server, and a processor. The processor is configured to control the communicator to transmit graphic data to be displayed on the display to the server, control the communicator to receive from the server video data into which the graphic data is converted, and process and display the received video data on the display.

A system and method provides a video chat capability where the video portion of the chat is initially impaired, but gets progressively clearer, either as time elapses, or as the users speak or participate with relevant information.

A device (1) and a method for transferring a raw image data stream (8) from an image sensor (6) via a data transfer connection (4) between a transmitter (2) and a receiver (3). In this case, the latency of the data transfer connection (4) is determined (S1), and the data rate of the raw image data stream (8) at the transmitter (2) is adapted (S3) to the determined latency.

Methods, apparatus, and systems for multi-resolution processing for video classification. A plurality of video frames of a video are obtained and a resolution for classifying each video frame of the plurality of video frames is determined by analyzing each video frame using a policy network. Based on the determined resolution, each video frame having a determined resolution is rescaled and each rescaled video frame is routed to a classifier of a backbone network that corresponds to the determined resolution. Each rescaled video frame is classified using the corresponding classifier of the backbone network to obtain a plurality of classifications and the classifications are averaged to determine an action classification of the video.

A scaling device of a real-time image and a scaling method are disclosed, the scaling device includes a storing unit, a receiving unit, a determining unit, a computing unit, and an outputting unit, wherein the storing unit stores multiple lookup tables respectively corresponding to different scaling algorithms. The receiving unit receives a real-time image from an image outputting device. The determining unit decides a scaling algorithm in accordance with the content of the real-time image and a required scaling scaling ratio, and reads one of the lookup tables from the storing unit based on the decided scaling algorithm. The computing unit performs a scaling process on the real-time image to generate a processed image in accordance with the lookup table read by the determining unit. The outputting unit outputs the processed image.

A shading correcting method for a real-time image is disclosed and includes following steps: obtaining a real-time image through an image sensor; reading a stored previous image which is time-adjacent to the real-time image; computing an image reference data of the previous image; computing an adjusting parameter in accordance with the image referring data and an equipment reference data of the image sensor; adjusting a gain table based on the adjusting parameter to generate an adjusted gain table, wherein the gain table records multiple compensation values each for compensating each corresponding pixel of the real-time image; correcting the real-time image in accordance with the adjusted gain table to generate an adjusted image; and, outputting the adjusted image.