111 results about "Visual fidelity" patented technology

The invention discloses an indoor real scene three-dimensional reconstruction method based on improved 3D Gaussian sputtering, belongs to the technical field of three-dimensional reconstruction, and aims to complement initial point clouds in a self-adaptive manner through a designed feed-forward point cloud densification network, generate a high-density 3D Gaussian radiation field, fill scene missing details and avoid the problem of precision attenuation caused by lack of point cloud constraints. In the cost body optimization stage, a depth regularization loss module is designed by integrating global structure features, depth information is integrated into the optimization process, algorithm reasoning is accelerated, and object structure fuzziness is relieved; and finally, in combination with adaptive density control and Gaussian pruning, radiation field parameters and density distribution are finely adjusted, indoor scene reconstruction with double improvement of visual fidelity and structural integrity is realized, interactive application becomes possible, a real-time solution is provided for indoor scene reconstruction, and application of a three-dimensional reconstruction technology is widened.

The invention relates to the technical field of building model design, in particular to a building three-dimensional model lightweight design method and system based on artificial intelligence, and the method comprises the steps: extracting geometric-semantic features of a building model through a multi-scale curvature filtering and semantic segmentation network, constructing a fusion feature vector matrix, and obtaining a fusion feature vector matrix; by utilizing an integrated graph convolutional network and a self-adaptive neural simplification network of a double-branch attention mechanism, differential resampling is executed based on vertex importance weight, a simplified intermediate model is generated, a surface microstructure is recovered by means of a generative adversarial network, grid holes are corrected by combining Delou inner triangulation, and a surface microstructure is obtained. A non-uniform rational B-spline curved surface is adopted to reconstruct a key decoration component and output a lightweight model, so that the problems of insufficient geometric feature retention and semantic information splitting in the traditional technology are solved, intelligent, efficient and lightweight of a building three-dimensional model is realized, visual fidelity is ensured while data compression is performed, and the construction quality is improved. And the digital management requirement of the whole life cycle of the building is met.

The invention discloses a cross-source data three-dimensional reconstruction method and system based on improved Gaussian sputtering, and the method comprises the steps: collecting an unmanned plane inclined image and a ground panoramic image of a target region, and constructing a time-space correlation data set; based on multi-view geometric constraints, space-time coding matching point pairs are established through an adaptive feature pyramid, intelligent incremental cross-source data sparse reconstruction is carried out, and point cloud and camera parameters are output; adopting improved Gaussian sputtering, compressing a three-dimensional Gaussian kernel into a two-dimensional Gaussian primitive through double tangent vector constraint, and fitting surface geometry to realize multi-scale reconstruction; and optimizing primitive parameters by using a differentiatable renderer, completing multi-scale fine reconstruction through gradient back propagation, and generating a high-precision three-dimensional model. According to the method, multi-scale accurate geometric prior input and accurate camera poses are provided for three-dimensional reconstruction, the dependence on professional manual operation in a traditional three-dimensional reconstruction method is greatly reduced, and meanwhile, the geometric accuracy and visual fidelity of a reconstruction result are remarkably improved.

The invention provides a three-dimensional object collision detection parcel grid generation method and system, a storage medium and a program product, and the method comprises the steps: extracting all vertex data of a first object according to a sub-Mesh data set after serialization of a three-dimensional model, and determining an initial center point; each vertex of each piece of sub Mesh data is converted from a local coordinate system to a global world coordinate system, and a point cloud data set is generated; constructing an initial convex hull by adopting a matrix hierarchical extremum retrieval algorithm, and generating a final convex hull by adopting a conflict graph and incremental convex hull algorithm; initializing a radius coverage model by taking the geometric center of the model as a sphere center; performing subdivision according to longitude and latitude to generate a hierarchical ball grid; emitting rays, correcting vertex positions layer by layer, approaching the surface of the model, and outputting a collider network. Through the overall point cloud set, the incremental convex hull algorithm and the spherical grid contraction technology, unified topological wrapping of the multiple three-dimensional objects is achieved, the visual fidelity and the collision precision are ensured, and resource consumption is reduced.

The invention discloses a 3D animation model intelligent generation method based on image recognition, and relates to the technical field of 3D animation models.Physical accuracy and visual fidelity of mechanical arm animation are remarkably improved through a multi-view feature fusion and physical constraint fusion mechanism; the space-time convolution kernel module is combined with mechanical kinematics constraint to effectively inhibit action distortion under high-speed motion; a dynamic anti-aliasing algorithm and a speed-adaptive LOD strategy are subjected to collaborative optimization, and edge aliasing and fuzzy mismatching are eliminated while the calculation load is reduced; external vibration data are converted into microscopic deformation through a micro-amplitude displacement superposition technology, and the limitation of traditional deformation simulation is broken through.

The invention discloses a digital archive safe circulation tracking method and system based on a dynamic watermark, and relates to the technical field of digital archives, and the method comprises the steps: collecting the physical layout features and semantic features of an archive at the same time, generating a comprehensive archive feature map, and dynamically adjusting the watermark intensity in combination with a rank screening threshold; a visual fidelity and watermark extraction degree double-index evaluation system is introduced, watermark position evaluation is carried out, and archive carrier sequence substandard and standard labels are obtained; and by monitoring the watermark survival rate, the visual fidelity and the circulation error rate, a correction strategy selection rule is constructed and comprises position iteration correction or sequence correction, so that evaluation and dynamic calibration of the watermark embedding position are realized, and dynamic selection of a correction strategy is realized.

The invention provides a pixel dynamic calibration method and device for a display, equipment and a storage medium. The method comprises the following steps: acquiring display parameters and a calibration image of the display; performing visual semantic analysis on the calibration image to generate a partition guidance mask, and marking a plurality of areas with different visual fidelity in the image by the partition guidance mask; generating a group of parallel region tone mapping curves for the plurality of regions based on the display parameters and the partition guide mask; performing synchronous processing on a corresponding region of the calibration image by using the region tone mapping curve to generate a partition mapping result, and fusing the partition mapping result into a correction image; generating a strategy execution record based on the partition guidance mask and the regional tone mapping curve; binding the strategy execution record with the content characteristics of the calibration image, and storing as a scene calibration strategy file; and when a new image frame is processed, calling the matched scene calibration strategy file for processing.

The invention discloses a lightweight single-image super-resolution reconstruction method based on local and global feature collaborative enhancement perception, which is used for solving the problems of insufficient utilization of high and low frequency clues in single-image super-resolution, low feature fusion efficiency and difficulty in consideration of structural consistency and visual fidelity of reconstructed images. The network adopts a double-flow heterogeneous architecture; a local branch uses multi-type differential convolution explicit coding image edge and texture prior to enhance detail characterization capability; the global branch effectively models long-range dependency and low-frequency semantic information by integrating local, cross-regional and global multi-level spatial self-attention mechanisms. The frequency sensing fusion module provided by the invention generates a channel specific space weight based on frequency characteristics, self-adaptively fuses double-branch characteristics, accurately balances structure maintenance and detail enhancement requirements in a characteristic fusion process, and effectively reduces characteristic redundancy. According to the super-resolution network, the model complexity is remarkably reduced, high-resolution images which are consistent in structure, vivid in vision and rich in details can be generated while lightweight design is kept, and an effective scheme is provided for efficient and high-performance lightweight single-image super-resolution reconstruction model design.

The invention discloses a 3D generative model training method and device based on a hybrid training framework, equipment and a storage medium, and belongs to the technical field of artificial intelligence. The method comprises the following steps: pre-training a 3D generation model by utilizing a preset 3D data set; quickly generating initial 3D assets according to the text cue words through a 3D generation model; a strategy based on two-dimensional knowledge distillation is adopted, a text-to-2D image generation model is used as a teacher model to carry out iterative distillation optimization on the initial 3D assets, and the 3D assets with improved visual fidelity are obtained; in the distillation process, dynamically adjusting the teacher model to adapt to the distribution of the initial 3D assets by using a self-adaptive teacher model guide strategy; and taking the optimized high-fidelity 3D assets as enhanced training samples, and training the 3D generation model again to improve the generation quality. According to the method, the 3D generation model is pre-trained, so that the 3D generation model is initially converged; according to the distillation method, strong text-to-2D image generation model knowledge is transferred to initial 3D assets and serves as an enhanced sample to train a 3D generation model again for knowledge internalization. The adaptive teacher model guiding strategy reduces the distribution difference between the teacher model and the student model, and ensures the generation quality of the 3D generation model.

The invention provides a virtual fitting method and device, equipment and a storage medium. The method comprises the following steps: acquiring a video containing a figure and a clothing image; determining a character potential feature map according to the video potential features obtained from the video without the clothing part and the depth posture in the video; determining a clothing feature map and clothing semantic latent features according to the clothing image; performing first self-attention calculation according to the character latent feature map and the clothing feature map to obtain a first feature map; performing first cross attention calculation according to the clothing semantic latent features and the first feature map to obtain a second feature map; performing space-time attention processing according to the second feature map to obtain a third feature map; and generating a virtual fitting image according to the third feature map and the clothing semantic latent features. According to the method provided by the invention, learning is carried out for clothing properties through space-time attention processing, and an efficient global space-time attention mechanism is realized, so that a more real and coherent try-on image is generated, and the visual fidelity and dynamic motion consistency of clothing are improved.

The invention discloses a design manuscript code generation and visual error iterative correction method and system based on multi-agent cooperation, and aims to solve the problems of low front-end code generation efficiency, poor visual restoration degree and lack of an automatic correction mechanism in the prior art. The system constructs a four-node state diagram based on LangGraph, automatically initializes a series engineering scaffold, obtains design data and generates a structured protocol, and generates a component code based on the protocol and performs visual verification and iterative correction on four processing nodes. The method comprises the following steps: dynamically generating an engineering scaffold through a large language model agent, converting Figma design data into a structured protocol, and carrying out iterative optimization by utilizing a judger-repairer mode until an error is lower than a threshold value; according to the method, high-fidelity automatic delivery from the design manuscript to the code is realized, and the executable front-end engineering code and the visual reduction degree analysis report are output.

The invention discloses an image fusion method and system based on multi-semantic guidance and mixed experts. The problems that in the prior art, robustness is insufficient, and visual fidelity and semantic integrity are difficult to balance are effectively solved. According to the method, infrared and visible light images to be fused and task identifiers are obtained, and firstly, a CLIP network is utilized to extract high-level semantic features as guide vectors; and then inputting the image and the guide vector into a pre-trained hybrid expert (MoE) fusion network. According to the network, intermediate features are extracted through an encoder, a gating network dynamically activates part of expert subnets according to task identifiers and semantic vectors and calculates routing weights, adaptive nonlinear transformation and weighted fusion are carried out on the features, and finally a high-quality fusion image is reconstructed through a decoder. The method can adapt to different task requirements, and the calculation efficiency is remarkably improved while the image fusion quality and the semantic consistency are improved.

The invention discloses a remote sensing image super-resolution reconstruction method based on a diffusion bridge model. The method comprises the following steps: firstly, constructing a diffusion bridge model, and connecting low-resolution and high-resolution image endpoints; secondly, explicitly aligning states of an image recovery bridge process and a pre-training generation diffusion process by designing a state alignment mechanism so as to multiplex powerful generation prior of a pre-training model; meanwhile, a lightweight feature adapter is introduced into a decoding end of the pre-training model, and high-frequency detail features reserved by an encoder are injected into a decoding path through a gating residual mechanism so as to suppress an over-smoothing phenomenon caused by VAE decoding. According to the method, the problems of insufficient prior utilization and high-frequency detail loss of a traditional diffusion model in remote sensing image super-resolution reconstruction are effectively solved, the structural integrity and visual fidelity of the image are ensured while the reconstruction efficiency is remarkably improved, and the method is suitable for a multi-scene remote sensing image super-resolution task.

The invention discloses a text-to-three-dimensional object (3D) generation method based on dual color consistency matching, and aims to solve the problem of 3D asset quality reduction caused by multi-view color inconsistency in the prior art. According to the method, in each training iteration, a group of multi-view images are firstly rendered from a 3D model, and a high-fidelity forward view is specified as a color reference; subsequently, optimization is carried out through a double matching mechanism: 1, matching among images: aligning colors of other views to the reference view by using depth semantic features, thereby breaking circulation of error accumulation; 2, image internal matching: in a single image, color and geometric smoothness in the same semantic region are standardized by improving total variation loss; through the dual mechanism, accumulation and propagation of unnatural color distortion are effectively prevented, color inconsistency is reduced, and the visual fidelity and color consistency of the generated 3D model are remarkably improved.

The invention discloses a hierarchical three-dimensional scene generation method and system based on spatial super-division, and belongs to the technical field of computer graphics, and the method comprises the steps: carrying out the preprocessing of a scene image, and obtaining a high-resolution object image; generating initial rough scene voxels for the scene image, and screening rough voxels and structural latent variables aligned with the high-resolution object image from the initial rough scene voxels to construct a hierarchical scene tree; inputting the high-resolution object image and the rough voxel into a voxel super-resolution model, and generating a fine voxel which keeps geometric consistency with the rough voxel; performing scale alignment and attitude registration based on the rough voxels and the fine voxels; and generating fine voxels of the sub-components recursively by taking the rough voxels of the current node as conditions based on the hierarchical scene tree, and finally assembling to generate a high-resolution three-dimensional scene. According to the method, a high-quality three-dimensional scene with high visual fidelity, fine geometric details and global structure consistency can be efficiently and automatically reconstructed from a single RGB image.

Techniques disclosed herein relate generally to modifying images to reduce display power while maintaining visual fidelity of the displayed images. In one example, a computer-implemented method includes receiving an input image to be displayed by a type of display device, obtaining a machine learning model that is trained to edit display content to reduce power consumption of displaying the edited display content by the type of display device while maintaining a visual fidelity of the edited display content, applying the machine learning model to the input image to generate an output image, and displaying the output image via a display device of the type of display device.

The invention discloses a three-dimensional Gaussian splash reconstruction method for an underwater scene, and belongs to the technical field of computer vision and three-dimensional reconstruction. Comprising the following steps: acquiring a monocular video frame sequence of a target underwater scene, a corresponding camera pose sequence, an initial sparse point cloud, an initial three-dimensional Gaussian point set and learnable physical parameters of an underwater imaging model; in the training process, performing weighted evaluation on a reconstruction error based on a multi-view consistency mechanism of opacity weighting, calculating an importance score of each Gaussian point, and performing densification operation on a three-dimensional Gaussian point set; adopting a staged freezing strategy to cooperatively optimize the three-dimensional Gaussian point set and underwater imaging model parameters; and performing rendering and underwater image synthesis on any new view angle camera pose based on the optimized three-dimensional Gaussian point set and underwater imaging model parameters, and outputting a new view angle synthesized image to represent a reconstruction result. According to the method, the geometric compactness, the visual fidelity and the physical interpretability of an underwater three-dimensional reconstruction result are improved.

The invention relates to the technical field of computer graphics and three-dimensional modeling optimization, in particular to a 3D model lightweight method and system based on point cloud hierarchical slicing and dynamic mapping mapping.When the 3D model lightweight method and system are used, the storage efficiency, the rendering performance and the visual fidelity are improved by establishing a point cloud and mapping bidirectional coupling mechanism, and the 3D model lightweight effect is improved. In the aspect of storage efficiency, an efficient geometric and texture association storage system is constructed by relying on a map curvature adaptive segmentation and dynamic slice binding technology, an excellent geometric and texture compression effect is realized, the storage cost of a high-precision three-dimensional model is greatly reduced, and in the aspect of real-time rendering performance, through a dynamic loading strategy during operation, the real-time rendering efficiency is improved. By combining efficient visibility screening acceleration and an intelligent resource preloading technology, the real-time scheduling efficiency of the model is greatly improved, and the working efficiency of scenes such as design iteration and model editing is remarkably improved.

The invention discloses a webgis-oriented real-time decoding and integrated visual system and a webgis-oriented real-time decoding and integrated visual method for meteorological data. Relates to the technical field of meteorological data processing, and comprises a data access and real-time decoding module used for obtaining a meteorological data file and analyzing the meteorological data file through a real-time decoding engine to obtain a standardized data object; the visual configuration module is used for constructing a visual template database; the rendering message publishing module is used for packaging the storage path of the standardized data object and the visual configuration ID into a rendering task message and publishing the rendering task message; the distributed rendering module is used for executing a graph generation operation based on the rendering task message and outputting a panoramic image; the tile generation module is used for cutting the panoramic image through a tile cutting engine; and the front-end display module is used for superposing the map tiles on the base map to obtain a meteorological view and displaying the meteorological view on a visual interface. Unification of data processing efficiency and high-end visual fidelity is realized.

The invention discloses a deep sea multi-beam sound intensity data reconstruction method and device fusing an attention mechanism. The method comprises the following steps: respectively designing damages of different sizes, including rectangular damages and irregular damages, for multi-beam backscattering intensity images of a shallow sea area and a deep sea area, taking the intensity images of the shallow sea area as a training set and a test set, and taking the images of the deep sea area as a verification set; a UNet structure is used as a trunk, and a residual module and a multi-scale channel space attention mechanism are fused to construct a UNet-MCSA intensity image restoration model; and repairing the damage intensity image by using a nearest neighbor interpolation method to obtain an NNI repaired image, and constructing a UNet-MCSA-NNI model through a histogram registration method by taking the UNet-MCSA repaired image as a basis and the NNI repaired image as a reference to obtain a deep sea multi-beam backscattering intensity repaired image with both high precision and visual fidelity. The depth and depth are combined, advantages are complementary, and a new normal form is provided for deep sea multi-beam backscattering intensity image restoration.

The invention discloses a deep learning-based area simplification method for a three-dimensional building model, and relates to the technical field of computer graphic processing. According to the method, an original building three-dimensional grid model is preprocessed, vertex semantic features are extracted through a graph convolutional neural network, and regional importance scores between 0 and 1 are generated; integrating scores into surface collapse algorithm error measurement, and constructing a dynamic collapse priority queue in combination with a normal change penalty term; updating an adjacent vertex error and a queue position based on queue iterative collapse; and stopping when the double termination thresholds are met, and outputting the simplified model. According to the method, key areas such as doors and windows, roof edges and the like can be accurately reserved, model lightweight and visual fidelity are balanced, a multi-source input model is adapted, manifold topology is kept, and simplified intelligence and universality are improved.

A modeling system converts polygons of a three-dimensional (3D) mesh model to points of a point cloud in an automated manner that increases the resolution and visual fidelity of the point cloud relative to the 3D mesh model. The system receives the polygons of the 3D mesh model, and generates points over the flat plane of each polygon according to a density and arrangement that increases the resolution of the points relative to the original polygon. The system receives an enhancement map with values for displacing the polygons of the 3D mesh model. The system displaces the generated points by mapping the values from positions in the enhancement map to corresponding positions of the generated points. The system generates the point cloud with the displaced points to provide improved visual quality and detail relative to the polygons of the 3D mesh model after enhancement with the enhancement map.

This invention relates to the fields of computer graphics and 3D modeling optimization technology, specifically to a lightweight 3D model method and system based on point cloud layering and dynamic texture mapping. In use, this invention establishes a bidirectional coupling mechanism between point clouds and textures, thereby improving storage efficiency, rendering performance, and visual fidelity. Regarding storage efficiency, it relies on texture curvature adaptive segmentation and dynamic slicing binding technology to construct an efficient associative storage system for geometry and texture, achieving excellent geometry and texture compression effects and significantly reducing the storage cost of high-precision 3D models. In terms of real-time rendering performance, it significantly improves real-time model scheduling efficiency through runtime dynamic loading strategies combined with efficient visibility filtering acceleration and intelligent resource preloading technology, thereby significantly improving work efficiency in scenarios such as design iteration and model editing.

The invention discloses a pathological image segmentation method and system based on coevolution generation type difficult sample mining, and the method comprises the steps: constructing a mask synthesis engine guided by biological information, and generating a cell nucleus mask through introducing a cell affinity matrix and structure prior based on a graph theory; establishing a segmentation-oriented adversarial renderer, and aligning the generated image with a real image in a feature space by using a multi-layer feature discriminator; implementing a closed-loop co-evolution strategy, dynamically identifying vulnerability categories by using performance feedback of the segmentation model, and guiding a generator to carry out adaptive difficult sample mining; and obtaining a cell nucleus segmentation result through alternate mutual promotion of the generator and the segmentation model and regression fine tuning of real data. According to the method, the problems that in existing small sample learning, generated data lacks biological rationality and visual fidelity cannot be converted into segmentation performance are solved, and the segmentation precision and generalization ability of the model are remarkably improved under the condition of extremely few labeled data.

The invention relates to a device, a method and a graphical user interface for displaying a representation of a person. Techniques for displaying a representation of a person based on background, viewing angle and / or mouth occlusion are disclosed. The method includes, at a computer system in communication with one or more display generation components: displaying a representation of a person via the one or more display generation components, including displaying a representation of a face of the person at a first visual fidelity; and in response to determining that the mouth of the person is occluded, displaying the representation of the face of the person at a second visual fidelity, the second visual fidelity being less than the first visual fidelity.

The present invention discloses a method and system for tracking the secure circulation of digital archives based on dynamic watermarks, which relates to the field of digital archive technology. The method comprises the following steps: simultaneously collecting the physical layout features and semantic features of the archives, generating a comprehensive archive feature map, and dynamically adjusting the watermark strength in combination with a rank screening threshold; introducing a dual-index evaluation system of visual fidelity and watermark extraction degree to evaluate the watermark position and obtain substandard and standard labels of the archive carrier sequence; and constructing correction strategy selection rules including position iterative correction or sequence correction by monitoring the watermark survival rate, visual fidelity and circulation error rate, thereby realizing not only the evaluation and dynamic calibration of the watermark embedding position, but also the dynamic selection of the correction strategy.

The application discloses special ice blocks for simulation ice lamps and a manufacturing method and application in the ice lamps, and belongs to the technical field of simulation ice. The special ice blocks for simulation ice lamps comprise a hollow body with an open top and a top cover matched with the opening, the top cover and the opening of the hollow body are sealed by edge sealing resin to form a sealed closed space; the hollow body and the top cover are made of transparent or semi-transparent thermosetting resin composite material, and the edge sealing resin is made of transparent or semi-transparent thermoplastic resin composite material. The special ice blocks for simulation ice lamps have a high simulation effect, visual fidelity, and almost no difference in shape from real ice, and have cost advantages and collection and processing advantages that cannot be matched by real ice. The material is firm, the environment-friendly green simulation ice does not shrink and deform due to temperature change, and can be widely produced and applied as an ecological and environment-friendly green simulation ice which is not limited by geographical position and climate conditions and is artificially made.

A method for producing printed wood veneer sheets comprises capturing high-resolution digital images of source wood veneer using polarized lighting and a digital camera with a polarizing filter; digitally processing and aligning the images to create a seamless composite image with enhanced color and grain detail; and printing the composite image directly onto a natural wood veneer substrate using a large-format UV flatbed printer with UV-curable inks. The method enables replication of rare, endangered, or extinct wood species on sustainable substrates while preserving the tactile qualities of natural wood and achieving superior visual fidelity. The printed veneer sheets may be used in furniture, cabinetry, architectural millwork, and other applications.

The invention discloses an intelligent switching method and system for face component structured mask learning, and the method comprises the steps: extracting a portrait mask with an edge perception capability, and reconstructing a high-fidelity background region with spatial continuity through combining a background reconstruction network; generating a standardized face image with geometric consistency by adopting a face detection and posture correction network; generating an optical head portrait with vision and texture consistency; performing structured mask learning on the standardized face image and the optical head image by using a semantic segmentation network to realize pixel-level face analysis; obtaining a multi-component region mask through mask calculation based on morphological operation; generating an optical head portrait with a natural transition effect by using an optical head portrait synthesis module based on Poisson fusion; and generating a hair changing portrait with physical authenticity by using a hair changing portrait synthesis module. According to the method, the visual fidelity, the detail consistency and the identity retentivity of the face image after hair changing are remarkably improved.

Mesh simplification reduces the complexity of 3D objects while maintaining visual fidelity. While there are effective techniques for mesh simplification for simple meshes, in actual use cases it may be difficult to simplify more complicated meshes. A technical solution retrieves an initial mesh (e.g. a triangle mesh) and constructs an edge list including physical and virtual edges for the initial mesh. The initial mesh is then decimated by iteratively collapsing the edges, prioritized based on a modified quadric error metric that may combine a memory edge quadric error and a memoryless area quadric error. The technical solution may maintain a correspondence map during the decimating and use it to perform texture transfer after simplification based on the correspondence map.