33results about How to "Improve video quality" patented technology

The embodiment of the invention provides a special effect video generation method and device, electronic equipment and a storage medium. A to-be-processed image is acquired; based on a to-be-processed image, a target image is generated, the target image is an image generated after a target special effect is applied to a target object in the to-be-processed image, and the target object in the target image has a target effect generated by the target special effect; a video generation model is called to process the to-be-processed image and the target image, a special effect video is generated, the special effect video comprises a video first frame, a video tail frame and at least one video middle frame located between the video first frame and the video tail frame, and the video first frame and the to-be-processed image have the same image content; the video tail frame and the target image have the same image content, and the at least one video middle frame is used for representing the continuous change process of the generated target effect. The content change of the special effect video is smoother and more real, and the video quality of the special effect video is improved.

The invention discloses a monitoring video real-time super-resolution reconstruction method and system fused with a space-time attention mechanism, and the method comprises the steps: firstly carrying out the extraction of shallow features, then carrying out the extraction of deep features, and carrying out the fusion of the shallow features and the deep features, so as to enhance the capturing capability of details in a monitoring video; the continuity and consistency of the video frames are enhanced by using time information between continuous frames, and the information of the time dimension is fused into the processing of the video frames, so that the dynamic capture capability and the overall video quality of a video monitoring system are improved; the time dimension is introduced into the SwinV3Transform, and the time information is integrated by modifying the attention mechanism, so that the time and space characteristics can be captured more accurately, and the continuity and visual effect of the video are improved.

The invention discloses a digital human video generation method and device, electronic equipment and a storage medium. The method comprises the following steps: determining a lip shape and a body language corresponding to a target audio, and generating an initial digital human video according to the lip shape, the body language and a predetermined target digital human; wherein the target digital figure is a digital figure determined according to a user demand; performing super-resolution processing on the initial digital human video through a generative facial prior generative adversarial network model to obtain a target video frame sequence; and generating a target digital human video according to the target video frame sequence and the target audio, and outputting the target digital human video according to a preset format. According to the technical scheme provided by the embodiment of the invention, the generated target digital human video has higher resolution and better video quality, and meanwhile, the facial details of the digital human can be recovered to keep the sense of reality of the image.

The embodiment of the invention discloses a video noise reduction method and device, computer equipment and a medium, and the method comprises the steps: obtaining a target video, and traversing image frames in the target video; when the current image frame of the target video is traversed, acquiring motion information of pixel movement between the current image frame and an adjacent image frame of the current image frame, and determining a pixel-level weight map for the current image frame based on the motion information; performing noise reduction processing on the current image frame by using the pixel-level weight map of the current image frame to obtain a noise-reduced image frame of the current image frame; obtaining a noise reduction image frame of each image frame in the target video, and generating a noise reduction video of the target video based on the noise reduction image frame of each image frame in the target video; the video quality can be improved.

The invention relates to the technical field of image processing, and particularly provides a video processing method and device, equipment and a storage medium, and the method comprises the steps: obtaining an initial video which comprises at least two first video frames; for at least two first video frames, the first video frames are input into a first neural network model to obtain a first feature map, and the first feature map comprises high-frequency information and dark channel information; inputting the first feature map into a second neural network model for super-resolution reconstruction processing to obtain a second feature map; inputting the second feature map and the first video frame into a third neural network model for defuzzification processing to obtain a second video frame; and combining the at least two second video frames to obtain a target video. According to the embodiment of the invention, the fuzzy region in the continuous frames is processed while the super-resolution is ensured, and the quality of the shot video is improved.

The invention discloses an H.266 / VVC video coding method based on space-time visual perception. The H.266 / VVC video coding method comprises the steps of extracting space-time features and saliency features, determining perception distortion and determining perception QP. According to the method, the space and time perception features of the CTU in each frame of image are adopted to determine the saliency feature matrix and the saliency value of the CU, and the technical problem that an existing saliency-based compression coding method depends on selection of a saliency region, and excessively pays attention to the saliency region but ignores perceptible distortion of a non-saliency region is solved. A perception distortion model is constructed by performing linear weighting on saliency features and spatial-temporal features, more subjective visual perception redundancy is removed, the video compression effect is improved, the video compression time is shortened, the video compression effect is further improved by using a saliency adaptive QP selection method, and the video compression efficiency is improved. The method has the advantages that the method better conforms to visual features of audiences in the video field with complex motion and texture, and the like.

The present invention provides an invisible two-dimensional code embedding, detection and repair method based on a neural network, comprising: using nonlinear time psycho-visual modulation technology to embed a two-dimensional code into a video so that the two-dimensional code cannot be observed by human eyes; collecting a set of data containing the two-dimensional code from the video after the two-dimensional code is embedded, and using a first neural network to locate the two-dimensional code in the data; using a second neural network to calibrate the located two-dimensional code to obtain a calibrated two-dimensional code; inputting the calibrated two-dimensional code into a third neural network for repair to obtain a repaired two-dimensional code. The invisible two-dimensional code embedding, detection and repair method based on a neural network provided by the present invention can effectively improve the embedding quality of the invisible two-dimensional code and the efficiency of detection and repair.

Disclosed in the embodiments of the present disclosure are a video processing method and apparatus, and an electronic device and a storage medium. The method comprises: determining a blurred video frame in an original video; removing the blurred video frame from the original video, so as to obtain an intermediate video, which dose not comprise the blurred video frame; on the basis of a video frame in the intermediate video that has a timestamp adjacent to a target timestamp, determining a video frame to be inserted, wherein the target timestamp is the timestamp of the blurred video frame; and inserting into a position in the intermediate video that corresponds to the target timestamp, the video frame to be inserted, so as to obtain a target video. By means of the video processing method provided in the present disclosure, the aims of removing a blurred frame from a video and improving the quality of the video are achieved.

The invention relates to airborne CameraLink optical fiber video-to-network transmission equipment, belongs to the technical field of video signal transmission, and is particularly suitable for a flight test and monitoring system. The equipment comprises a photoelectric signal conversion module, a master control analysis module, a video compression module and a network transmission module. The photoelectric signal conversion module is used for acquiring a CameraLink optical fiber video signal sent by flight equipment, converting the CameraLink optical fiber video signal into a differential transmission mode logic electric signal, and transmitting synchronous clock information at the same time; the main control analysis module is used for analyzing a video signal and generating RGB format video data and a compression parameter sequence; the video compression module is used for carrying out H.264 or H.265 format compression on the video data; and the network transmission module binds the compressed video stream with the flow control information, generates a self-adaptive transmission stream sequence and outputs the self-adaptive transmission stream sequence. According to the invention, the video signal transmission efficiency, the anti-interference capability and the bandwidth utilization rate are improved.

The invention discloses a video editing method, electronic equipment and a storage medium. The method comprises the following steps: acquiring video material data to be edited; story orchestration logic is determined; and editing the video material data based on the story orchestration logic to obtain an edited video. Therefore, the video material data can be edited based on the determined story arrangement logic, so that the logic of the video clips of the edited video can be continuous and naturally linked, and the video quality of the edited video can be effectively improved.

The invention provides a video generation method and device, electronic equipment and a storage medium, and belongs to the technical field of financial science and technology. The method comprises the following steps: acquiring audio data for generating a character video, target character image data and reference video data; separating target audio with character acoustic features from the audio data; motion parameters are generated based on the target audio and the target person image data, and initial face motion parameters of the target person are obtained; performing correction processing on the initial face motion parameter based on the reference video data to obtain a target face motion parameter; on the basis of the target audio, key postures are generated through a preset figure posture generation model, and figure posture motion parameters of the target figure are obtained; and performing video generation based on the target face motion parameter and the figure posture motion parameter to obtain a figure video of the target figure. The generation accuracy of the figure video can be improved.

The embodiment discloses a method and a device for video coding and decoding by utilizing meta information. In this embodiment, an image decoding device decodes compression parameters for a current block, and then generates meta-information by combining one or more of the compression parameters. Here, the meta-information includes each original compression parameter, or includes a meta-information vector generated from each compression parameter. The image decoding apparatus inputs meta-information into a deep learning-based extraction model to generate a meta-information feature vector, and then performs a decoding process on a current block using the meta-information feature vector.

The present embodiment provides a video encoding method and apparatus using chroma component prediction based on a luma component. In this embodiment, an image decoding device derives a corresponding luma block of a current chroma block based on a color format. An image decoding apparatus obtains a luma component pre-recovery region for a corresponding luma block and a chrominance component pre-recovery region for a current chrominance block based on a block segmentation structure of a luma component and a chrominance component and prediction information of the corresponding luma block. The image decoding apparatus performs modeling of a relationship between samples within a luma component pre-recovery region and samples within a chroma component pre-recovery region, and then generates a prediction block of a current chroma block from samples of a corresponding luma block by using the modeled relationship.

The invention relates to a video generation method and device, electronic equipment, a medium and a program product, and the method comprises the steps: displaying a preset creation page which comprises video generation reference information, and the video generation reference information comprises a target reference video; in response to the video generation instruction, a generated target video is displayed, the target video is generated based on at least two video reference materials carrying timestamps, and the at least two video reference materials and the timestamp corresponding to any video reference material are separated based on the target reference video by the multi-modal separation model; the timestamps corresponding to the at least two video reference materials are used for aligning the at least two video reference materials. By using the technical scheme provided by the embodiment of the invention, the video generation efficiency can be improved while the diversity of the generated video content and the video quality are improved.

The embodiment of the present application relates to the technical field of computer data processing, and discloses a video identification method, which comprises the following steps: determining voice text information and picture information of a to-be-identified video; performing feature fusion on the voice text information and the picture information to obtain fusion video features of the to-be-identified video; and determining an originality determination result of the to-be-identified video according to the fusion video features and a preset video database. In the above manner, the accuracy of original video determination is improved.

Embodiments of the present disclosure disclose a digital tourism-based synthetic video derivation method, an electronic device and a readable medium. A specific implementation of the method includes: in response to determining that the video detection result represents no abnormality, controlling a video processor to perform cutout processing on user action video stream data, and performing fusion processing on the obtained user cutout video stream data and a preselected virtual background to obtain synthetic video stream data; in response to detecting that the theme rendering video stream data meets a preset target condition, controlling a video derivation device to generate a short chain of the theme rendering video stream data, and performing video derivation of the generated video short chain through a preset application channel to obtain a digital tourism synthetic video. The implementation shortens the time of video synthesis, and improves the processing capability and video quality of the derived synthetic video.

The invention relates to a video compression model processing method, computer equipment, a computer readable storage medium and a computer program product. The method comprises the steps that a to-be-trained student model and a trained teacher model are acquired, the teacher model and the student model are video compression models based on a neural network, the teacher model is configured to realize video compression of a first code rate, the student model is configured to realize video compression of a second code rate, and the first code rate is greater than the second code rate; video compression is carried out on the sample video through the student model and the trained teacher model, training losses are constructed based on compression results obtained in respective compression processes, and the training losses comprise distillation losses between the student model and the trained teacher model and reconstruction losses of the student model; and performing parameter adjustment on the student model according to the training loss until the model converges to obtain a trained student model. By adopting the method, it can be ensured that the compressed video has low code rate and high video quality at the same time.

A method and apparatus for encoding an intra prediction mode for each chroma component are disclosed. In a disclosed embodiment, a video decoding device decodes, from a bitstream, first intra prediction mode information for a first chroma channel of a current chroma block. The video decoding device decodes, from the bitstream, second intra prediction mode information of a second chroma channel of the current chroma block. Here, the first intra prediction mode information includes at least one of a first CCLM (Cross-Component Linear Model) mode flag, a first CCLM mode index, and a first chroma intra prediction mode indicator, and the second intra prediction mode information includes at least one of a second CCLM mode flag, a second CCLM mode index, and a second chroma intra prediction mode indicator.

The invention relates to the technical field of shooting lenses, and provides a shooting lens adjusting method and system based on machine vision. On the basis of the timestamps of the video data shot by all the shots, feature information of targets in all the video data at all the timestamps is detected, target functions are generated, and the shot corresponding to the optimal target function is selected as the target shot at the current moment; and taking the video data collected by the target shot as main data, taking the video data collected by the shots except the target shot as standby data, and performing picture synthesis based on the timestamp to generate a panoramic video. The method comprises the following steps: determining main data and standby data by intelligently evaluating feature information captured by each shot, filling missing or optimizing a picture by using the standby shot data, and iteratively processing video data of a next timestamp to realize virtual adjustment and seamless connection between an optimal shot and the standby shot. And the video quality and integrity of video processing under the multi-lens view angle are obviously improved.

The invention provides a training method of a video enhancement model, a video enhancement method and related equipment, and relates to the technical field of video processing. The method comprises the following steps: acquiring a training video set; the training video set comprises a plurality of training videos, the training videos comprise a plurality of training video frame pairs, and each training video frame pair comprises a first training video frame and a second training video frame which are adjacent; performing enhancement processing on the first and second training video frames based on a video enhancement model to obtain first and second processed video frames; performing reconstruction processing on the first processed video frame and the second processed video frame based on a conductive encoder to obtain a reconstructed video frame and code rate information; determining loss information according to the reconstructed video frame and the second training video frame; and training a video enhancement model according to the loss information and the code rate information to obtain a trained video enhancement model. According to the method, a derivable encoder is introduced to train a video enhancement model, the video quality and the coded code rate are considered in the training process, and end-to-end optimization is achieved.

The invention discloses a block position-based intra-frame mode adaptive coding method and a block position-based intra-frame mode adaptive coding device. In this embodiment, an image decoding apparatus determines a type of a current block based on a position of the current block, and generates a most probable mode (MPM) list including MPM candidates. The image decoding apparatus determines a redundant prediction mode from the MPM candidates according to the type of the current block. The image decoding apparatus determines a representative mode from among the redundant prediction modes, and reconfigures the MPM list by removing the redundant prediction mode excluding the determined representative mode. The image decoding apparatus decodes the MPM index of the current block from the bitstream, and determines the intra prediction mode of the current block from the reconfigured MPM list by using the MPM index.

The invention relates to the technical field of video data transmission, and discloses a video frame scale transformation heterogeneous system and method.The video frame scale transformation heterogeneous system comprises a video source, the video source is transmitted through a network after being compressed and coded, and then the video source is transmitted to a video receiver for playing after being decoded. An IFPWRR algorithm is provided, and the algorithm distinguishes frame types of video stream data. The video frame scale transformation heterogeneous system and the video frame scale transformation heterogeneous method are researched on the basis of a video stream transmission technology of a heterogeneous network, and mainly relate to selection of reliable paths in video stream transmission, research on influence factors of video stream transmission in the heterogeneous network, multi-path load balancing processing of video stream transmission, optimal coding / decoding and video compression transmission. In combination with the mobile internet technology, the bandwidth occupied by video transmission is reduced during network video transmission, the delay of video transmission is reduced, and the video quality of a receiving end is comprehensively improved.

The embodiment discloses a video encoding method and apparatus using template-based prediction. In the present embodiment, a video decoding device decodes an index indicating a distance between a current block and a template region (adj). A video decoding apparatus identifies a template region based on a distance between a current block and the template region and a shape of the template region. The video decoding apparatus searches for an optimal template in the search region using the template region based on the template matching, and then generates a prediction block of the current block from a reference block corresponding to the optimal template.

Methods for deriving an intra prediction mode based on an inter prediction signal are disclosed. In the present embodiments, an image decoding device determines a motion vector for a current block from a motion vector candidate list for the current block and generates an inter prediction signal for the current block based on a reference block indicated by the motion vector for the current block. The image decoding device derives an intra prediction mode for the current block based on the reference block and a template for the reference block and generates an intra prediction signal for the current block based on the intra prediction mode. The image decoding device generates a final prediction signal for the current block based on the inter prediction signal and the intra prediction signal.

The present invention discloses a cathode etching device and method for display screens, and belongs to the technical field of cathode etching for display screens. It includes a cathode etcher, a vacuum pump, a laser processing mechanism, a lifting unit and a translation driving component; the cathode etcher is provided with a feed port and a working window, and the interior thereof is a cathode etching chamber; a support is provided in the cathode etching chamber, and the support is used to support the display screen; the vacuum pump is connected to the cathode etcher, and is used to evacuate the cathode etching chamber; the laser processing mechanism is arranged corresponding to the working window, and is used to emit laser to etch the display screen; the lifting unit is arranged below the support and is connected thereto; the translation driving component is connected to the support by transmission, and the translation driving component is used to drive the support to drive the display screen to translate between the feed port and the working window. The present invention can safely transport and efficiently process the display screen, thereby effectively improving the light transmittance of the display screen and the image quality of the camera.

The present embodiment discloses a method and apparatus for video coding using rearrangement of a prediction signal in an intra block copy mode. In this embodiment, a video decoding device obtains a splitting direction indicating a horizontal splitting or a vertical splitting of a current block, and obtains a ratio of sub-blocks with respect to the current block. A video decoding device generates an initial prediction block of a current block according to an intra block copy (IBC) mode. The video decoding device splits the initial prediction block into sub-blocks according to the splitting direction and the proportion of the sub-blocks, and then rearranges the order of the sub-blocks to generate a final prediction block of the current block.

The embodiment of the invention provides a self-adaptive loop filtering classification method in video coding and decoding and a related device, and relates to the technical field of video coding and decoding, multimedia, cloud technology, artificial intelligence and the like. The method comprises the steps of obtaining classification information corresponding to a target image, and then determining a target category of an adaptive loop filter corresponding to the target image based on the classification information. The classification information includes at least one of a target range, intermediate information, or a subset of categories. Wherein the target image corresponds to an image sequence, a frame of image, and a strip image, a rectangular image or a block image in the frame of image in the video. According to the embodiment of the invention, the determination accuracy of the category of the ALF is improved, so that the technical effect of improving the video quality is achieved.

The present disclosure relates to a video processing method, device and equipment and storage medium, and belongs to the technical field of computers, which is used for deinterlacing processing of interlaced videos to improve video quality and increase video definition. The video processing method comprises the following steps: obtaining a video to be processed; determining a video type of the video to be processed based on a pre-trained target type detection model; the video type is a non-interlaced type or a target interlaced type in multiple interlaced types; when the video type is the target interlaced type in the multiple interlaced types, inputting multiple image frames to be processed into a target deinterlacing model corresponding to the target interlaced type for deinterlacing processing to obtain a non-interlaced video corresponding to the video to be processed.

The invention discloses a human-machine cooperation video generation system, and belongs to the technical field of artificial intelligence and e-commerce video generation. The method comprises a cloud step and an end side step. The cloud step comprises a script copywriting generation step, a shooting guidance generation step and a video mixing / matching verbal skill generation step. The end side comprises the steps of collecting materials according to guidance and feeding back the materials in real time, distributing videos and uploading the videos to a video platform. The method has the advantages that millions of stores of a brand party can be assisted to quickly generate high-quality videos on a large scale, marketing is carried out on all large platforms to obtain exposure, and brand exposure and customer obtaining channels are increased.

The embodiments of the present disclosure disclose a method, device, equipment and medium for storing video data based on content recognition. A specific implementation of the method includes: collecting a video data set to be labeled; for each video data to be labeled in the video data set to be labeled, performing the following labeling and storage steps: performing metadata labeling processing on the video data to be labeled; determining the resolution information corresponding to the resolution labeling information as the target resolution; performing image quality enhancement processing on the video frame set to be labeled in the video data to be labeled to obtain an enhanced video frame set to be labeled; performing content recognition processing on the enhanced video frame set to be labeled; based on the enhanced video frame set to be labeled, updating the video data to be labeled to obtain updated video data to be labeled; based on the metadata labeling record information and the content recognition identifier, labeling and storing the updated video data to be labeled in a preset storage device. This implementation improves the video quality of the stored video data.