Abstract: Provided are an image processing method, an electronic device, and a non-transitory computer-readable storage medium. The implementation includes that: a segmentation position of a segmentation line in a display region is determined, a first partial image extracted from a first to-be-displayed image is displayed on a first side of the segmentation line according to the segmentation position, and a second partial image extracted from a second to-be-displayed image is displayed on a second side of the segmentation line according to the segmentation position, where the encoding manner of the first to-be-displayed image is different from that of the second to-be-displayed image; and the content of a synthesized image synthesized by the first partial image and the second partial image is the same as the image content of the first to-be-displayed image and the content of the synthesized image is the same as the image content of the second to-be-displayed image.

Abstract: Embodiments of the present disclosure relate to a method and apparatus for processing a video. The method may include: acquiring object regions obtained by performing object detection on a target video frame, a type of an object in each of the object regions being a preset type; determining, for an object region in the acquired object regions, in response to determining that the object region satisfies a preset condition, that the object region is a non-ROI; using an object region other than the non-ROI in the object regions of the target video frame as a ROI; and acquiring a quantization parameter change corresponding to each ROI, and encoding the target video frame based on the quantization parameter change.

Abstract: A method for detecting a jitter in a video includes obtaining video frames of a video, in which the video frames include a target video frame and a plurality of historical video frames before the target video frame, determining moving distances in a preset distance of the video frames relative to corresponding previous video frames, determining a target amplitude and a target period in the preset direction for the target video frame; and determining that there is a jitter in a video in response to the target amplitude in the preset direction determined for the target video frame being greater than a preset amplitude and the target period being less than a preset period.

Abstract: Embodiments of the present disclosure provide a method for transcoding a video. An input attribute of a video is obtained and a target attribute is obtained. A segment transcoding speed of the video is determined based on the input attribute and the target attribute. The segment transcoding speed indicates a transcoding speed of a video segment. The number of video segments of the video is determined based on a preset target transcoding speed and the segment transcoding speed. The video is segmented based on a video length of the video and the number of video segments to obtain the video segments. The video segments are transcoded based on the segment transcoding speed.

Abstract: The present disclosure provides a method and an apparatus for enhancing image quality, a device, and a medium, relates to the field of artificial intelligence and specifically to computer vision and deep learning technologies, and can be applied to an image processing scenario. The method includes: determining an ROI and an RONI in an image to be processed; inputting the ROI to an ROI image quality enhancement model, to obtain first image data output from the ROI image quality enhancement model; inputting the RONI to an RONI image quality enhancement model, to obtain second image data output from the RONI image quality enhancement model; and blending the first image data and the second image data.

Abstract: The present disclosure provides a map data fusion method and apparatus, an electronic device, a medium and a program product. The method includes: acquiring first map data and second map data; based on a first feature descriptor set and a second feature descriptor set included in the first map data and the second map data respectively, determining a set of matching point pairs between a first set of three-dimensional coordinate points and a second set of three-dimensional coordinate points included in the first map data and the second map data respectively; determining a pose transformation matrix between the first map data and the second map data based on the set of matching point pairs; and fusing the first map data and the second map data into third map data based on the pose transformation matrix.

Abstract: Embodiments of the present disclosure relate to a method and apparatus for processing a video frame. The method may include: acquiring a sequence of video frames of a video; ascertaining, in the sequence of the video frames, a previous frame, and ascertaining, in the sequence of the video frames, a subsequent frame corresponding to the ascertained previous frame based on acquired number of frames from the previous frame to the subsequent frame. An update step is performed as follows: acquiring object regions detected respectively in the ascertained previous frame and the ascertained subsequent frame, and confidence levels of the object regions; fusing a confidence level of a first object region and a confidence level of a second object region, and updating the confidence level of the second object region based on the fusion result; and updating the ascertained previous frame and the ascertained subsequent frame.

Abstract: Embodiments of the present disclosure provide a method for transcoding a video. An input attribute of a video is obtained and a target attribute is obtained. A segment transcoding speed of the video is determined based on the input attribute and the target attribute. The segment transcoding speed indicates a transcoding speed of a video segment. The number of video segments of the video is determined based on a preset target transcoding speed and the segment transcoding speed. The video is segmented based on a video length of the video and the number of video segments to obtain the video segments. The video segments are transcoded based on the segment transcoding speed.

Abstract: Embodiments of the present disclosure relate to a method and apparatus for processing a video. The method may include: acquiring object regions obtained by performing object detection on a target video frame, a type of an object in each of the object regions being a preset type; determining, for an object region in the acquired object regions, in response to determining that the object region satisfies a preset condition, that the object region is a non-ROI; using an object region other than the non-ROI in the object regions of the target video frame as a ROI; and acquiring a quantization parameter change corresponding to each ROI, and encoding the target video frame based on the quantization parameter change.

Abstract: Embodiments of the present disclosure relate to a method and apparatus for processing a video frame. The method may include: acquiring a sequence of video frames of a video; ascertaining, in the sequence of the video frames, a previous frame, and ascertaining, in the sequence of the video frames, a subsequent frame corresponding to the ascertained previous frame based on acquired number of frames from the previous frame to the subsequent frame. An update step is performed as follows: acquiring object regions detected respectively in the ascertained previous frame and the ascertained subsequent frame, and confidence levels of the object regions; fusing a confidence level of a first object region and a confidence level of a second object region, and updating the confidence level of the second object region based on the fusion result; and updating the ascertained previous frame and the ascertained subsequent frame.

Abstract: Embodiments of the present disclosure relate to a method and apparatus for processing a video. The method can include: acquiring a to-be-processed video, and dividing the video into at least one video segment according to a scene; for a video segment of the at least one video segment, extracting a feature of the video segment; inputting the feature and a target video quality into a pre-trained encoding parameter prediction model, to obtain an encoding parameter of the video segment, the encoding parameter prediction model being used to represent a corresponding relationship between the feature of the video segment and the encoding parameter under the target video quality; and performing an encoding process on the video according to the encoding parameter corresponding to the video segment of the at least one video segment, to generate an encoded video.

Abstract: Embodiments of the present disclosure relate to a method and apparatus for processing a video. The method can include: acquiring a to-be-processed video, and dividing the video into at least one video segment according to a scene; for a video segment of the at least one video segment, extracting a feature of the video segment; inputting the feature and a target video quality into a pre-trained encoding parameter prediction model, to obtain an encoding parameter of the video segment, the encoding parameter prediction model being used to represent a corresponding relationship between the feature of the video segment and the encoding parameter under the target video quality; and performing an encoding process on the video according to the encoding parameter corresponding to the video segment of the at least one video segment, to generate an encoded video.