13results about How to "Improve video quality" patented technology

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 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.

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 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 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 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.

The invention discloses a model training method, a video processing method, electronic equipment and a storage medium, and relates to the technical field of video processing and large models. The method comprises the following steps: acquiring training video data; performing video reconstruction processing on the training video data by using an initial video variational self-encoding model to obtain a reconstruction result, the initial video variational self-encoding model being used for performing key frame space compression and overall time sequence compression on a plurality of video frame groups in the training video data to complete video reconstruction; and training the initial video variational self-encoding model based on the training video data and the reconstruction result to generate a target video variational self-encoding model, the target video variational self-encoding model being used for providing reconstructed video data for the initial video generation model to train and generate the target video generation model. According to the method and the device, the technical problems of low reconstruction result quality and slow optimization of the video variational auto-encoder model in the related technology are solved.