1087 results about "Video editing" patented technology

The invention provides a method for adapting a text-to-image (T2I) diffusion model for video editing by using spectral decomposition to achieve controlled spectral shifts in the model's weights. This adaptation involves maintaining constant singular vectors while selectively adjusting singular values in response to a text prompt. A spectral shift regularizer constrains adjustments, particularly limiting changes to larger singular values to ensure minimal deviation from the original model's structure. This approach allows efficient, prompt-driven video editing by modifying specific elements according to the prompt while preserving the original video context. By focusing on selective spectral adjustments, the method reduces adaptation time and computational demands, making it suitable for real-time and resource-sensitive applications, such as dynamic video editing for streaming services.

Media user interfaces are described, including user interfaces for capturing media (e.g., capturing a photo, recording a video), displaying media (e.g., displaying a photo, playing a video), editing media (e.g., modifying a photo, modifying a video), accessing media controls or settings (e.g., accessing controls or settings to capture photos or videos to capture videos), automatically adjusting media (e.g., automatically modifying a photo, automatically modifying a video), and automatically managing a media capture mode (e.g., a photo media capturing mode, a portrait media capturing mode, a video media capturing mode) based on a set of conditions.

The invention discloses a video editing method and related equipment, and the method comprises the steps: receiving an editing intention of a user, carrying out the semantic analysis of an intention analysis model, and generating an editing copywriting, a style and a structured instruction; the edited copywriting is split according to the edited copywriting; performing cross-modal analysis on video materials by using a video understanding model trained based on an open-source multi-modal model, and accurately positioning sub-lens segments; secondly, editing the sub-lens segments through an editing model to generate a preliminary sheet, performing quantitative scoring through a video scoring model, and obtaining a scoring result according to a multi-dimensional index; and finally, the result is fed back to the editing model, and iterative adjustment is carried out until a final slice is produced. According to the method, the editing efficiency is improved, the manual operation time is shortened, the material adaptability is enhanced, the personalized requirement is met, the editing effect consistency is improved, the video content understanding is deepened, the editing effect is optimized, the technical threshold is reduced, the existing technical problems are solved comprehensively, and an efficient, intelligent and personalized editing scheme is provided.

The present invention relates to a computer-implemented method and system for generating a video editing project using artificial intelligence (AI) and machine learning (ML) techniques. The method includes processing a collection of video clips to generate text-based metadata, receiving selection criteria to identify relevant video clips, and generating a natural language prompt based on the selection criteria. The prompt, comprising instructions and context, is provided to a large language model (LLM), which processes the input and outputs data for constructing a video project data model. The project data model includes timing data for salient snippets within the selected video clips. A dynamic and interactive web-based user interface is rendered to visually represent the project data model, offering a timeline view and editing tools for refining the video project. This system streamlines the video editing process by integrating AI-driven content analysis with user-directed editing, resulting in a tailored video project that aligns with user-defined thematic elements.

The invention discloses a short video intelligent editing method and system based on multi-modal analysis, and relates to the technical field of video editing. The method is used for improving editing efficiency and visual experience and comprises the following steps: extracting lip motion features of a character, visual saliency features of a commodity and a voice emotion intensity value from a target short video stream to form multi-modal time sequence data; afterwards, the voice stream is recorded, a product keyword timestamp is extracted, the alignment degree is calculated through dynamic time warping in combination with a visual saliency peak value, and a preliminary editing point set is generated through weighted evaluation in combination with an emotional intensity value; constructing an editing decision optimization model based on deep reinforcement learning, taking the multi-modal features as state input, adjusting the retention probability of editing points through a joint reward function, and selecting an optimal transition mode; and the lip movement and voice synchronization error before and after the editing point and the emotional and visual continuity of the transition section are analyzed, the discontinuous region is smoothed, and the edited finished product is output, so that precise short video intelligent editing is realized.

The invention relates to the technical field of artificial intelligence and the field of financial science and technology, and discloses a method for adjusting the playing speed of voice content in a video, and the method comprises the steps: obtaining a video file containing to-be-adjusted voice content, carrying out the voice recognition of an audio track of the video file, and converting the audio data of the voice content into text data; dividing the text data into a plurality of sentences or phrases; identifying keywords in each sentence or phrase, performing emotion content classification on the sentences or phrases containing the keywords, and determining the importance level of each sentence or phrase; according to the emotion content and the importance level, adjusting the playing speed of the corresponding voice content, and generating adjusted audio data; aligning the adjusted audio data with the video image to generate synchronous audio and video data; and a final video is generated. Through automatic voice recognition, sentiment analysis and playing speed adjustment, the steps of manual participation are reduced, and the video editing efficiency is greatly improved.

The invention relates to an automatic video editing method based on semantic analysis, and belongs to the technical field of video editing. The method comprises the following steps: extracting anchor point information of text content in a streaming media file based on a knowledge graph, establishing a support relationship, and determining a main anchor point, a sub anchor point and a argument anchor point by combining the support relationship and the anchor point information; constructing a dynamic trigger mechanism, setting a verification direction of the dynamic trigger mechanism, determining a semantic extension direction of the anchor point information according to the verification direction, and verifying whether a precondition chain supporting the anchor point information exists or not; and setting a credibility scoring strategy, determining the credibility of the anchor point information according to the logic complexity, the language confidence and the text consistency, forming a sequence set of the anchor point information, and splicing to form a logically coherent video editing text result. According to the method, automatic and intelligent editing of the video is realized based on semantic analysis, and the editing efficiency and quality are remarkably improved.

The invention discloses a video portrait consistency editing method based on optical flow guidance and text driving, and the method comprises the steps: firstly, employing a face key point extraction method and a depth estimation method to extract a face key point and a depth map of each frame of an input video, and guaranteeing the consistency of the facial expression of an edited portrait and a source image; a diffusion control network is used to edit and generate the face depth map, the key points and the user input text description as conditions, and the consistency of multi-view editing is realized through the potential code alignment of an attention mechanism and the guidance of optical flow change; thirdly, constructing a diffusion model with consistent time by utilizing the inter-frame optical flow change and the depth map change; through the above steps, the problems of multi-view and time consistency in video editing are solved, and high-quality video portrait editing is realized.

The present technology provides for AI-assisted video editing tools that implement a novel method of processing video which includes transcribing segments of a video and labeling the segments based on the contents of the segments. A smart edit can be generated based on the labelled segments. The smart edit can serve as a rough cut for a user to make further edits.

The invention discloses a video highlight detection method based on a weak supervision multi-mode large model, and the method comprises the steps: constructing the pairing data of a video clip and text description based on a video language large model, and configuring a highlight detection module for carrying out the significance score calculation of a video frame according to a highlight detection instruction, a highlight detection model is obtained through training in a multi-stage progressive training mode and is used for highlight detection of a video. According to the method, the precision and efficiency of highlight detection are remarkably improved by generating a high-quality pseudo tag and designing a time-sequence-sensitive highlight detection module and a progressive multi-stage training strategy, and the method has wide practical application value in scenes such as content optimization and personalized recommendation, video editing and manufacturing, social media, education and training and the like.

The invention provides a video generation method and device, electronic equipment and a storage medium, and belongs to the technical field of multimedia. The method comprises the following steps: displaying a video editing interface, wherein a material generation control and a video track are displayed in the video editing interface; in response to a trigger operation on the material generation control, an artificial intelligence technology is adopted to generate a first material, and the first material comprises at least one of an image material and a video material; in the video track, displaying the first material; and in response to a video generation operation, generating a video based on the first material in the video track. According to the technical scheme, the image / video material generation function is deeply integrated into the video editing scene, material generation and video generation can be seamlessly connected, and therefore the video generation efficiency can be improved.

The invention discloses a video generation method and device, a readable medium, electronic equipment and a program product, and the method comprises the steps: displaying a video editing interface, and displaying a target text in the video editing interface; in response to a split mirror generation operation in the video editing interface, a split mirror list is displayed based on the target text, the split mirror list comprises a plurality of split mirror cards, and a split mirror picture and split mirror subtitles obtained by splitting the target text are displayed in each split mirror card; and in response to a video generation operation in the video editing interface, generating a video based on the split list. Therefore, the video can be automatically generated based on the target text of the video editing interface, so that the complexity of video generation operation is simplified, and the video generation difficulty is reduced. Besides, as the split card comprises the split picture and the split subtitle, whether the split picture is matched with the picture described by the split subtitle or not can be quickly identified in an image-text combination form, and the accuracy and creation efficiency of the video content are improved.

The invention discloses a short video editing synthesis method based on fuzzy logic. The method comprises the following steps: S1, carrying out digital video preprocessing on an input original short video; s2, forming a short video feature data set; s3, generating a fuzzy logic decision result; s4, performing multi-target and multi-parameter optimization on the fuzzy logic decision result by adopting a random score programming method to form an optimized editing parameter set; s5, generating a preliminarily synthesized short video; s6, generating a video quality evaluation result; and S7, carrying out iterative optimization on the preliminarily synthesized short video according to a video quality evaluation result, adjusting the editing parameters and re-executing the editing synthesis step until the video quality evaluation result meets a preset standard, and generating a final edited finished product. According to the method, the editing scheme can achieve the best balance in the aspects of visual rhythm, information integrity and emotion expression consistency.

The invention discloses a multi-angle video automatic editing method based on content defect detection, and relates to the technical field of video processing. According to the method, multi-track video materials are accurately synchronized to the same time axis through cross-correlation calculation, and flaws in video content are analyzed frame by frame and classified and identified by applying fuzzy detection of a dynamic threshold and combining jitter detection and shielding detection of rotation and displacement estimation. And according to a detection result, an editing scheme is intelligently generated through a dynamic programming algorithm of state transition optimization, high-quality fragments are selected, defective parts are automatically removed, the continuity and multi-view diversity of video contents are reserved, and finally, a high-quality recorded video is generated through integration. The video editing efficiency is greatly improved, the manual intervention requirement is reduced, meanwhile, it is ensured that the quality of the output video meets the professional application requirement, and the method is suitable for multiple scenes such as conference recording, educational training and multi-angle video production and has high practical value and popularization prospects.

The invention provides an intelligent self-adaptive video editing method and system based on deep learning, and relates to the technical field of video processing.The method comprises the steps that firstly, a semantic mapping relation between a to-be-edited video material and a preset editing requirement is established, and an editing requirement mapping result is generated, the preset editing demand comprises a content style and a rhythm control demand, and then semantic feature association processing is carried out based on the mapping result to obtain a semantic association feature set comprising lens unit content semantic features and rhythm association features; then calling a pre-trained editing decision model (including a semantic matching module and a rhythm adjusting module) to carry out editing strategy matching on the set, generating a preliminary editing strategy set, generating an initial video editing scheme according to the preliminary editing strategy set, carrying out parameter adjustment on the initial scheme according to a strategy optimization suggestion output by the model, and carrying out video editing on the initial scheme; and a final video editing scheme is obtained, and intelligent self-adaptive editing of the video is realized.

The invention discloses a video editing and artistic creation system based on AI intelligence, which relates to the technical field of video editing and comprises a data acquisition module, a feature analysis module, a feature library construction module, a rule matching module and a split mirror generation module, the data acquisition module is used for acquiring traditional opera stage video data and corresponding audience feedback audio waveform data, and the feature analysis module is used for extracting spatial-temporal feature vectors of stylized actions from the traditional opera stage video data. The feature library construction module is used for constructing an action feature library containing action type codes and music beat deviation level codes according to the spatio-temporal feature vectors; the method has the beneficial effects that dynamic association analysis is performed by constructing the action feature library and combining audience feedback audio data, the short video sequence conforming to the art rule is automatically generated, and the method has the advantage of improving the Chinese opera performance video editing efficiency and the art expressive force.

The embodiment of the invention relates to a video editing method and device, equipment and a medium. The method comprises the following steps: displaying a target video editing interface; obtaining a target text and a target virtual object, and presenting a text segment formed based on the target text and a video segment formed based on the target virtual object in the editing area; performing video editing based on the text segment and the video segment, and presenting a video editing effect through the video preview area; wherein the video editing effect is at least used for presenting a picture and sound of reading the target text by the target virtual object, and the picture displays subtitles determined based on the text segment. According to the embodiment of the invention, the threshold that the user uses the virtual object to create is reduced, more users can flexibly and conveniently use the virtual object to create the video, and the video creation form is enriched.

The invention provides a video processing method, a recording and broadcasting system, electronic equipment and a computer readable storage medium, and relates to the technical field of video processing, the method comprises the following steps: obtaining a panoramic classroom video and video editing information, the video editing information comprising related description information of a target video expected to be generated through the panoramic classroom video by a user; generating a mirror moving parameter and a shooting parameter of the virtual camera according to the video editing information; determining a first interested picture which accords with the description of the video editing information from the panoramic classroom video according to the mirror operation parameters; performing image reconstruction processing on the first interested picture according to the mirror operation parameter and the shooting parameter to obtain a second interested picture; and generating a target video according to the second interested picture. According to the method and the device, the teaching video which has the mirror moving effect and meets the requirements of the user is quickly generated under the conditions that manpower is not consumed and a mirror moving technology is not needed.

A disclosed computer-implemented method may include presenting, within a video creation interface, a list of video styles, each video style within the list of video styles representative of a trained model, the trained model trained to apply different aesthetic attributes to video content in accordance with a different video style. The method may also include receiving, via user input to the video creation interface, a selection of a particular video style from the list of video styles and, in response to receiving the selection, applying, to video content received via the video creation interface, a video editing technique corresponding to the particular video style. Various other methods, systems, and devices are also disclosed.

The invention relates to the technical field of video analysis, in particular to a video editing method based on grid layout alternate diffusion and multi-attention control, and the method comprises the steps: segmenting an original video frame sequence into a plurality of grids, each grid comprising a plurality of pixel space video frames which are continuously arranged, and forming grid data; mapping the gridding data to a low-dimensional submerged space through an encoder, and generating initial submerged space feature data; the initial submerged space feature data are edited, the editing process comprises a diffusion process and a sampling process, the diffusion process is based on a pre-trained stable diffusion model, and a time attention module is embedded in the diffusion process; in the sampling process, executing an odd-even time step alternate replacement strategy on the grid layout to promote cross-grid global consistency, and dynamically fusing attention maps of a reconstruction branch and an editing branch according to a timestamp threshold to generate de-noised data; and decoding, splitting and recombining the de-noised data through a decoder to generate an edited continuous video frame sequence.

The embodiment of the invention provides a video editing method. The video editing method comprises the following steps: acquiring background music according to a video editing demand; on the basis of drumbeat recognition and emotion analysis on the background music by an expert template, selecting a key drumbeat for video picture switching, and generating an editing configuration file on the basis of the key drumbeat; segmenting and classifying the to-be-processed video through multi-modal analysis to obtain different types of video clips; and automatically selecting a video clip combination based on the editing configuration file, and adding a transition special effect to obtain an edited video. According to the embodiment of the invention, by introducing the intelligent editing scheme based on the expert template, the editing result can be ensured to be highly matched with the music rhythm, the scene segment selected in the editing process meets the preset emotion and theme requirements, and the logicality and ornamental value of the video are improved.

The invention relates to the technical field of editing and special effect generation, in particular to a digital media content intelligent editing and special effect generation system based on artificial intelligence. Comprising a content understanding analysis module, an editing decision module, a special effect generation preview module, an audio processing module, a dynamic transition special effect module, a subtitle generation editing module, a virtual interaction module and a content distribution optimization module. The content understanding analysis module is used for video content identification and sentiment analysis; and the editing decision module is used for recommending an editing point and providing a dynamic editing strategy. The video content can be automatically analyzed, the editing point and the special effect adding position can be identified, the editing and special effect generation efficiency is greatly improved, the editing strategy and the special effect type can be dynamically adjusted according to the video content and the sentiment analysis result, the editing and the special effect can better meet the user requirement and the video content, and the user experience is improved. Abundant editing and special effect options are provided, and the editing and special effect generation process is simplified.

The invention relates to an intelligent video editing method fusing human face features and human voice features, which comprises the steps of input preprocessing, multi-modal analysis, fusion scoring and automatic editing, and adopts a multi-modal mode for analysis, so that the recall rate of key segments is improved, and the efficiency of editing is improved. A personalized editing strategy is supported, facial expression changes and voice emotion peak values are aligned through dynamic time warping, a CLIP-like structure is used for training a bimodal encoder, the human face and the voice are mapped to a unified vector space, the association weight of the human face and the voice is automatically learned, and the intelligent degree of editing is improved.

A processor-implemented method performed for text-based video editing includes receiving a video input and a text prompt. The video input includes a sequence of video frames. Features of the video input are extracted to generate a latent representation of the video input. Noise is injected to the latent representation of the video input to generate a noise injected latent. The noise is conditioned on the video input. An artificial neural network (ANN) model processes the noise injected latent based on the text prompt to adapt the video input according to the text prompt.

A computer-implemented method includes determination of n noised codes corresponding to n video frames of an original video. A text code corresponding to a description text guiding video editing is determined. Denoising processing, using n Unet models obtained by using the text code and copying a Unet model, is performed on the n noised codes, where a pre-trained text-to-image model includes the Unet model, which includes a self-attention layer connected after a target network layer, and where the denoising processing includes performing, in a self-attention layer of any ith Unet model, attention calculation based on an output of a target network layer of the ith Unet model and an output of a target network layer in a predetermined target Unet model. Decoding processing is separately performed on the n denoised codes by an image decoder to obtain n target images to form an edited target video.

The embodiment of the invention provides a video generation method and device based on a digital human, a storage medium and a program product. In the embodiment of the invention, application scene information and role description information provided by a target merchant are acquired, a plurality of global port broadcast manuscripts corresponding to the application scene information are generated by using an AI language model, and at least two video description files are generated based on the plurality of global port broadcast manuscripts and the role description information; and automatically generating at least two template videos in batches based on the at least two video description files, returning the at least two template videos to the terminal equipment, and generating a target video based on the digital human by the target merchant based on the at least two template videos. Wherein the template videos generated in batches provide rich editing templates for users, merchants do not need to operate complex video editing software, and the complexity of video generation is reduced.

The embodiment of the invention provides a vehicle-mounted video production method and device, electronic equipment and a storage medium. The method comprises the following steps: identifying a highlight moment picture from video frames shot by cameras with different visual angles inside and outside a vehicle according to a preset period; determining a target camera according to the camera where the highlight moment picture is located, and recording a video by using the target camera to obtain a video material; fusing the video picture tag corresponding to the video material and the vehicle state tag according to a timestamp to obtain a vehicle end tag file; and performing video editing on the video material at least based on the vehicle end label file to generate a target video. Therefore, according to the scheme, automatic recording and video production of the vehicle-mounted video can be realized by identifying the highlight picture, and the generation efficiency and quality of the vehicle-mounted video are improved.

The invention relates to the technical field of audio and video production, and discloses a distributed audio and video production system, which comprises a user operation interface and a media processing center, and is characterized in that the media processing center integrates audio and video data from a plurality of creation nodes, such as video recording equipment, audio acquisition equipment and the like, provides comprehensive data support for users, and improves the user experience. And real-time audio and video editing, manufacturing and publishing are realized. The core of the system is composed of a network communication layer, a service processing layer, a media access layer and a media storage layer, the network communication layer provides flexible connection services, the service processing layer adopts a distributed architecture and supports efficient data acquisition and processing, the media access layer realizes rapid data access, and the media storage layer ensures safe storage and expansion of data. By optimizing key links such as data management and control, communication connection, service processing and data storage, the audio and video production efficiency and quality are remarkably improved, and the large-scale, multi-node and high-real-time production requirements are met.

The invention discloses a video editing method and device, electronic equipment and a nonvolatile storage medium. The method comprises the following steps: acquiring an audio data stream of a target video, and segmenting the audio data stream into a plurality of audio clips; determining a classification result corresponding to the audio clip, and determining a time period corresponding to the audio clip as a candidate ball hitting time period when the classification result is that the audio clip contains the ball hitting sound; acquiring a video frame corresponding to the candidate ball hitting time period in the target video, and judging that the candidate ball hitting time period is a real ball hitting time period under the condition that the visual feature of the video frame is matched with a preset ball hitting rule; and determining an editing time point according to the real ball hitting time period, and editing the target video according to the editing time point to obtain a ball hitting round video clip. The technical problem that the accuracy of ball hitting detection segment detection is low due to the fact that ball hitting detection is conducted only through sound and is easily interfered by environmental noise in the prior art is solved.

The present invention provides a multi-modal portrait video editing method, which can be applied to the technical field of video editing. The method comprises: given a portrait video, preprocessing same to obtain camera parameters, a human identity coefficient, a human expression coefficient, a human pose coefficient, a human semantic segmentation map, and a two-dimensional portrait mask; on the basis of a neural Gaussian texture mechanism, embedding a learnable three-dimensional Gaussian feature into a parameterized human geometric surface, using a neural renderer to convert a three-dimensional Gaussian splatting feature map into an image, and optimizing the reconstruction of a three-dimensional portrait on the basis of RGB and segmentation map information of the video; and using an iterative dataset update technique to distill knowledge of a multi-modal two-dimensional image generation model into three-dimensional portrait editing, and using expression similarity guidance and a face-aware portrait editing model to improve editing quality. The method elevates a two-dimensional editing task to three-dimensional space, and ensures good three-dimensional consistency and temporal consistency. By means of the knowledge of the multi-modal generation model, high-quality portrait video editing functions can be achieved.