147 results about "Global illumination" patented technology

The invention relates to the technical field of computer graphics, in particular to a real-time three-dimensional graphic rendering optimization method and device based on deep learning, and the method comprises the steps: carrying out the feature extraction of the geometric, texture and illumination information of a graphic through a multi-modal deep neural network, and generating a high-dimensional feature vector; dynamically adjusting the resolution of the triangular mesh by adopting a graph neural network, and outputting an optimized geometric mesh structure; predicting global illumination of the graph by using a neural radiation field model, and generating an optimized illumination map through a variational auto-encoder; performing fusion analysis on the illumination map and the texture data by using a visual Transform model to generate an adaptive texture mapping scheme; and in combination with a rendering scheduling strategy of deep reinforcement learning and a super-resolution reconstruction method of a generative adversarial network, a rendering result is optimized, and a rendered image is post-processed. According to the method, multiple deep learning technologies are comprehensively utilized, and the quality and efficiency of real-time three-dimensional graph rendering are remarkably improved.

The invention discloses a complex material-oriented global full-frequency illumination neural rendering method and system, and belongs to the technical field of computer graphics, and the method comprises the steps: querying and extracting a primary frequency feature and a secondary frequency feature in a neural feature field according to the primary geometric buffer and the reflection geometric buffer of a rendering pixel; performing weighted combination on the primary frequency features and the secondary frequency features through a double-frequency fusion module to form full-frequency fusion features; inputting the full-frequency fusion feature and the initial geometric buffer into a decoder to obtain a pixel radiation brightness value; and optimizing the network by adopting a double-stage training strategy of low-frequency data and multi-frequency data, and then using the optimized network for neural drawing of global full-frequency illumination. The method can improve the accuracy and stability of global illumination simulation in a complex dynamic scene, and is suitable for modeling a multi-frequency global illumination effect in a dynamic three-dimensional scene.

The invention discloses a driving method of a display panel and a display device, and the method comprises the steps: enabling each sub-pixel of the display panel to be connected with a global light-emitting control signal, and enabling the global light-emitting control signal to be used for controlling a first light-emitting device of the sub-pixel to be turned on, so that the display panel is in a first display stage; or controlling a second light-emitting device of the sub-pixel to be lightened to enable the display panel to be in a second display stage; at least part of the first display stage is located in a first display frame, at least part of the second display stage is located in a second display frame, and the first display frame is adjacent to the second display frame; the driving method comprises the following steps: after a first display frame starts and before a second display frame starts, controlling a global light-emitting control signal to jump so as to switch the display panel from one of a normal display mode and a peep-proof display mode to the other, thereby realizing a narrow frame of the display screen with a peep-proof function.

The invention belongs to the technical field of face recognition, and particularly relates to a face recognition algorithm adaptive to illumination variation, which uses Gaussian filtering to reduce noise caused by illumination variation, convert a color image into a grey-scale image, reduce calculation complexity, perform adaptive histogram equalization, estimate global illumination conditions in the image and improve the face recognition accuracy. Calculating the main direction and intensity of illumination in the image, predicting the current illumination condition, and enabling the image brightness to adapt to different environment illumination; identifying a face region in the image, using a deep learning method to position face related points, using an LBP to extract local features insensitive to illumination variation, and using a deep convolutional neural network to extract global features; introducing a multi-illumination data set; the Euclidean distance is used for comparing the extracted feature vectors, the similarity between the extracted feature vectors and known faces in a database is recognized, according to the similarity score, threshold judgment is adopted for AQW to obtain a final recognition decision, and the method has the effect of being capable of accurately adapting to facial features under different illumination conditions in real time.

The invention provides a surface roughness measuring method and device based on a multispectral laser speckle image, and belongs to the field of surface quality visual inspection. Comprising the following steps: respectively acquiring speckle images formed by irradiating the surface of a workpiece with lasers of N wavelengths at different angles, and constructing a multispectral laser speckle data set; the speckle images of N wavelengths at a single angle are spliced according to channels and subjected to feature fusion, and then a multispectral laser speckle fusion image is generated; the fused images of the multiple angles form an image sequence, and single images in the sequence are subjected to multi-scale feature extraction and fusion to generate single-angle features; the multi-angle features generate global illumination information through a multi-angle feature aggregation module, and finally a roughness value is calculated through a multi-layer perceptron. Multi-spectral laser speckle coding surface features are adopted, multi-angle information is fused through the multi-angle feature aggregation neural network, and the relation between the light source wavelength, the incident angle and the surface three-dimensional shape and roughness is comprehensively considered, so that high-precision measurement is achieved.

The invention relates to the field of graphic rendering, in particular to a high-efficiency graphic rendering system based on artificial intelligence core computing power, which comprises an intelligent task decoupling module for performing task decoupling on a graphic rendering task; the AI enhanced texture generation optimization module is used for learning a dynamic scene change rule to generate a texture map in real time, reducing calculation overhead in a repeated texture region by using a multiplexing algorithm, and performing super-resolution compensation on low-resolution textures by using a deep convolutional neural network; the AI driving illumination and shadow calculation module is used for predicting an illumination transmission path in a scene by using AI and reconstructing a dynamic shadow effect so as to realize high global illumination and shadow simulation; the task result synchronization module is used for synchronizing rendering data output by each subtask; according to the method, the high-quality texture map is dynamically generated, super-resolution compensation is carried out on the low-resolution texture, repeated calculation is avoided through a texture multiplexing algorithm, the calculation overhead is remarkably reduced, and the real-time rendering efficiency of a large-scale complex scene is improved.

The invention relates to an underwater image processing technology in the field of underwater autonomous perception, in particular to an underwater low-quality image enhancement method based on a Laplacian pyramid and contrast learning. Comprising the following steps: S1, image input and multi-scale decomposition: decomposing an input image into a low-frequency residual layer and a plurality of high-frequency detail layers through Laplacian pyramid decomposition; s2, inputting the low-frequency residual error layer into a global illumination and color correction sub-module to obtain an enhanced low-frequency residual error layer; s3, inputting the enhanced low-frequency residual error layer and the multi-scale high-frequency detail layer into a frequency domain enhancement feature module to obtain multi-scale enhanced high-frequency detail layer output; s4, performing progressive reconstruction on the enhanced low-frequency layer output and the high-frequency enhancement layer output of each scale according to the inverse process of the Laplacian pyramid; and S5, outputting a result and applying. The method can be used for sharpening optical image data in the operation task of the autonomous underwater vehicle, and the image quality is improved.

The invention discloses a virtual scene construction method based on point cloud data, a medium and equipment. The method comprises the following steps: constructing an initial virtual scene based on original point cloud data; constructing a depth map corresponding to the point cloud data in the initial virtual scene, and determining a shielding relationship among the objects in the initial virtual scene based on the depth map; performing physics-based rendering on an object in the initial virtual scene, and processing the rendered initial virtual scene by adopting global illumination; and integrating the occlusion relationship into the rendered initial virtual scene to generate a new virtual scene. Through the above mode, the method can improve the trueness of building the virtual scene through the radar point cloud data.

The invention discloses an endoscope image processing method and system for improving image quality, and relates to the technical field of image processing.The method comprises the steps that a highlight reflection area of an endoscope image is extracted by setting a detection and extraction mechanism of the highlight reflection area; the method comprises the following steps: dividing an image of which a highlight reflection region is extracted into a base layer and a detail layer, performing global illumination adjustment on the base layer, performing detail enhancement on the detail layer, and fusing the enhanced base layer and detail layer to obtain a pre-enhanced image; if the pre-enhanced image extracts an over-high-brightness area, repairing a high-brightness reflection area and outputting the high-brightness reflection area; according to the method, global enhancement of the endoscope image is realized through highlight reflection area detection, image hierarchical processing and highlight reflection area repair, and the visibility and availability of the endoscope image are improved.

The invention relates to an illumination rendering method and device, electronic equipment and a storage medium, and the method comprises the steps: dividing a virtual scene into scene coverage ranges corresponding to a plurality of hierarchies, generating an asynchronous illumination reconstruction task based on the current illumination state information of each hierarchy, and executing the asynchronous illumination reconstruction task. In the execution process, pre-calculated illumination data stored by a plurality of illumination probes in a corresponding scene coverage range are obtained, and a three-dimensional space corresponding to the scene coverage range comprises a plurality of tetrahedral grids with the illumination probes as vertexes; and determining a matched tetrahedral mesh of voxels in the corresponding three-dimensional space in the plurality of tetrahedral meshes, determining indirect illumination data based on the pre-calculated illumination data of each illumination probe in the matched tetrahedral mesh, and storing the indirect illumination data to the voxels to obtain the target volume texture of the hierarchy. And performing illumination rendering based on the target volume texture of each level. The dynamic global illumination effect of the open world game scene can be realized on the mobile terminal, and the picture quality of the game is improved.

The invention provides a light and shadow effect display method and electronic equipment, and relates to the technical field of terminals. According to the method and the device, the light and shadow effect display can be adaptively realized based on the preset illumination information in combination with the current display information, the interface light and shadow effect is enriched, and the use experience of a user is improved. The method comprises the steps that first operation of a user is detected, and the electronic equipment determines to refresh a first interface which is being displayed; the electronic device obtains illumination information and current display information, wherein the illumination information is a pre-configured global illumination definition. And the electronic equipment performs illumination rendering according to the illumination information and the current display information. Afterwards, the electronic device displays a second interface, and the first component in the second interface has a light and shadow effect formed after illumination rendering.

The invention discloses an efficient three-dimensional scene anti-rendering method and system based on a multi-view image and a storage medium, and the method comprises the steps: employing a neural symbol distance function network as a geometric model to represent a scene geometric structure of the multi-view image, decomposing a neural radiation field into a diffuse reflection field and a specular reflection field, in combination with the self-shielding probability of the mirror reflection field, the diffuse reflection field, the mirror reflection field and the self-shielding probability of the mirror reflection field, calculating color information of the spatial points and optimizing the geometric model; a material network is adopted to represent albedo and roughness and obtain material information, color information cached in a neural radiation field, an illumination visibility function and direct illumination are introduced, global illumination of each light ray is calculated, importance sampling and illumination Monte Carlo integral are combined to obtain a rendering result, and the material network and a direct illumination network are optimized; and on the basis of the geometric structure, the material information and the illumination information obtained by the decoupled geometric model, the material network and the direct illumination network, a high-quality image is generated by adopting rendering pipeline calculation.

The invention provides a hybrid screen space global illumination method based on resampling and a probe, and relates to the technical field of global illumination, and the method comprises the steps: firstly, in an offline environment, pre-calculating a baking light field probe; rendering a geometric buffer area, and updating a light field probe; using screen space ray tracing to generate an initial sample; performing time resampling and space resampling; obtaining an indirect diffuse reflection illumination result; carrying out delayed coloring by utilizing the generated geometric buffer area, indirect diffuse reflection illumination, light source data and shadow information; and sampling indirect diffuse reflection illumination by using the screen space coordinates of the pixels, and superposing the indirect diffuse reflection illumination with a direct illumination result, thereby obtaining a final coloring result.

The invention relates to the field of image correction, and provides an image correction method, device and system and a storage medium, and the method comprises the steps: synchronously collecting a color image and three-dimensional point cloud data of a target object through an RGB-D sensor, constructing an elastic mesh model (including a rigidity attribute), and achieving the high-precision surface expansion based on finite element analysis. Generating a geometric correction image; in combination with a multispectral shadow separation and generative adversarial network (GAN) restoration technology, shielding shadows are eliminated, and textures with consistent illumination are generated; and finally, optimizing global illumination uniformity through dynamic compensation perceived by ambient light. Through the technical scheme, the error of expansion correction of a non-planar object is reduced, the real content and the shadow area are efficiently distinguished, the dynamic ambient light change is adapted in real time, and the complex texture generation capability is improved.

The invention provides an illumination rendering method for a game scene and electronic equipment, and belongs to the technical field of global illumination. According to the method, the voxelization processing area is determined based on the observation point, only voxelization processing needs to be carried out on the scene in the limited range around the observation point, the calculation complexity can be greatly reduced, and memory resource occupation is reduced; tasks are distributed through a main thread, and a plurality of background threads execute voxelization processing in parallel, so that the utilization rate of a GPU can be improved, and blockage of the main thread can be avoided; by determining the processing priority of the voxel blocks, the voxel blocks which greatly influence the picture effect can be processed preferentially, real-time updating of the illumination effect of the central area of the visual field of a player is ensured, and delay or distortion of the key area of the picture is avoided.

The invention relates to a space-frequency domain collaborative low-light deblurring method based on Fourier transform and Mama architecture, and belongs to the technical field of image processing. According to the method, an image is decomposed through Fourier transform, and effective separation of low light degradation and fuzzy degradation is achieved at a frequency domain source according to the physical characteristics of amplitude spectrum dominant illumination and a phase spectrum dominant structure. In order to solve the problem of accurate reconstruction of frequency domain information in a spatial domain, a space-frequency domain double-branch collaborative architecture is constructed, global illumination recovery and local detail enhancement are respectively focused through low-frequency and high-frequency processing branches which are explicitly distinguished in the spatial domain, and frequency domain decoupling advantages and spatial domain sensing capability are adaptively bridged by combining a dynamic feature fusion mechanism. Meanwhile, in order to process different degradation types in the recovery process, a task-oriented decoupling optimization strategy is designed, the strategy activates amplitude adjustment and low-frequency optimization in the encoding stage to deal with low-light enhancement preferentially, and activates phase reconstruction and high-frequency enhancement in the decoding stage to process blurring removal in a targeted mode.

The invention discloses an infrared bidirectional thermal effect simulation method based on radiation and GPU acceleration, and belongs to the field of thermal radiation simulation and parallel computing. Dispersing the complex geometry into patch units, constructing an inter-patch radiation energy balance equation based on a radiance theory, and iteratively solving the final temperature of the patches through a radiance method; a three-level parallel strategy of a task level, a data level and an instruction level is designed, data intensive tasks such as shape factor calculation and radiance iteration are migrated to a GPU to be executed, data storage is optimized in combination with a structure array (SoA) layout and a sparse matrix compression technology, and efficient data sharing of a CPU end and a GPU end is achieved through a CUDA zero copy technology. According to the method, the dependence of a traditional method on regular grids is broken through, the calculation efficiency and precision of million-level surface patch heat radiation transmission in a complex scene are remarkably improved, and an efficient tool is provided for heat radiation indirect transmission calculation and a global illumination model in the field of three-dimensional scene infrared simulation.

The embodiment of the invention provides a global illumination rendering method, electronic equipment and a storage medium, belongs to the technical field of computer graphic processing, is applied to illumination rendering of a three-dimensional modeling scene, and comprises the following steps: obtaining an original picture without adding a global illumination effect, a corresponding camera viewpoint and a corresponding camera viewpoint; acquiring originally corresponding illumination radiation data based on a camera viewpoint, and determining the originally corresponding illumination radiation data as irradiance cache data; in response to the change of the camera viewpoint, performing ray tracing processing based on the changed camera viewpoint to obtain changed illumination radiation data; performing fusion processing on the irradiance cache data and the changed illumination radiation data to obtain target illumination radiation data; and performing global illumination generation based on the target illumination radiation data to add a global illumination effect to the original picture to obtain a target picture. According to the embodiment of the invention, the calculation complexity of indirect illumination can be reduced, and a global illumination effect is obtained.

The invention discloses a land environment shadow region optical feature recovery method and system, and the method comprises the steps: synchronously collecting a visible light image, a near infrared spectrum image and three-dimensional point cloud data of a target land region through a multi-mode sensor, and generating multi-source fusion data with a space-time alignment attribute; based on the multi-source fusion data, constructing an illumination transmission physical model of the scene, and separating a direct illumination attenuation component and an indirect illumination diffuse reflection component of a shadow region; performing compensation reconstruction on the direct illumination attenuation component by using a generative adversarial network, and generating an initial recovery image after shadow elimination; and outputting a final recovered image with global illumination consistency and local detail authenticity by adopting a cross-scale attention fusion mechanism. By using the embodiment of the invention, the real spectral attribute and rich spatial texture details of the ground feature can be maintained, and the visual consistency of the image and the reliability of subsequent quantitative application are improved.

The invention discloses a low illumination enhancement method based on event and image bidirectional collaborative guidance, and belongs to the technical field of computer vision. The method comprises an event feature extraction branch and an image-event fusion branch which are respectively provided with an image-guided event enhancement module and a Mama-based image-event fusion module; the two modules realize cross-modal interaction through bidirectional cooperative guidance. The image-guided event enhancement module suppresses event noise and compensates for context loss by using semantic context information of an image. The Mama-based image-event fusion module adjusts the global illumination and contrast of the image by using the global representation capability of Mama and the characteristics of linear space-time complexity, and fuses event data to the image in combination with a signal-to-noise ratio map to supplement structural information. According to the method, enhancement and fusion of the image and event information are realized through a bidirectional collaborative guidance mechanism, and the enhancement problems of image structure deficiency and illumination contrast degradation in a low-illumination scene are solved.

The invention discloses a medical image intelligent diagnosis and three-dimensional visualization interaction method and system based on artificial intelligence and Unreal Engine. The system is composed of a data acquisition module, an artificial intelligence analysis module, a three-dimensional reconstruction module, a rendering interaction module and a report generation module. The method comprises the following steps: firstly, carrying out voxel normalization on a DICOM / NIfTI image; the improved 3D U-Net is combined with CBAM attention and WGAN-GP training, and a focus initial density field is output; an AI enhanced implicit voxel reconstruction (AEIVR) algorithm is proposed, an enhanced density field is generated by using position coding + MLP, and grid extraction is completed by using improved Marking Cubes of a dynamic threshold; high-fidelity real-time rendering is realized in combination with a Nand micro polygon and Lumen global illumination in Unreal Engine, and VR / AR interaction and virtual surgery (real-time updating of resection mask driving) are supported. According to the method, the problems of large artifacts and insufficient interactivity and real-time performance of existing two-dimensional output and three-dimensional reconstruction are solved, and the end-to-end segmentation-reconstruction-rendering-interaction-reporting process is realized. On typical CT / MRI data, the segmentation Dice is about 0.90-0.94, the reconstruction voxel resolution is 0.1-0.5 mm, the artifacts are reduced by about 20%-30%, the PSNR is improved by about 3-7 dB, and the rendering interaction delay lt is achieved; the system is suitable for scenes such as lung CT, brain MRI, orthopaedic X-ray and cardiac ultrasound, and can be expanded to preoperative planning, remote consultation and teaching.

The invention relates to the technical field of image processing, and discloses a tea maturity detection method and system, and the method comprises the steps: obtaining an original image of tea in a natural illumination imaging environment; generating a global illumination difference chart representing an ambient illumination state, and performing illumination compensation on the to-be-detected area of the tea in the original image to obtain a compensated image of the tea; performing gray scale range adjustment on the compensated image of the tea leaves to obtain an enhanced spectral image of the tea leaves; integrating the color and spectral characteristics of the specific spectral reflection characteristics of the tea leaves with different maturity degrees in the enhanced spectral image and the three-dimensional morphological characteristics reflecting the spreading degree and thickness of the tea leaves into the fusion image characteristics of the tea leaves; mapping the color spectrum emission characteristics and texture characteristics of the tea leaves in the enhanced spectrum image to a maturity discrimination knowledge base of the tea leaves to obtain a preliminary maturity result; performing confidence coefficient weighting on the preliminary maturity result to obtain a target maturity; according to the invention, the tea maturity detection efficiency can be improved.

The invention provides an image enhancement method based on double-domain illumination prior and electronic equipment, and relates to the field of image processing. The method comprises the steps of obtaining a to-be-processed illumination image; according to local illumination distribution characteristics of the to-be-processed illumination image, multi-scale enhancement is carried out on the to-be-processed illumination image after global illumination enhancement, a first illumination image after spatial domain enhancement is obtained, and the local illumination distribution characteristics comprise a brightness mean value and a brightness standard deviation; amplitude information of the to-be-processed illumination image in the frequency domain is enhanced, and a second illumination image enhanced in the frequency domain is obtained; and fusing the to-be-processed illumination image, the first illumination image and the second illumination image to obtain an enhanced target illumination image.

The invention discloses a global illumination calculation method, a graphic processing device, a readable storage medium and a program product, which can avoid light leakage, mottling and the like under the condition that manual marking is not needed. The global illumination calculation method comprises the following steps: collecting a plurality of sampling points in a virtual scene and arranging a plurality of illumination probes; baking the plurality of sampling points based on light source information in the virtual scene to obtain illumination information of each sampling point; classifying the plurality of sampling points according to the illumination information and the position information of each sampling point; calculating illumination information and weight information of each illumination probe based on the illumination information and the position information of the sampling points of each category, wherein the weight information represents the contribution degree of the illumination information, corresponding to each category, of each illumination probe to illumination coloring of coloring points in the virtual scene; and performing illumination calculation on the virtual scene according to the illumination information and the weight information of the plurality of illumination probes.

Disclosed approaches provide for interactions of secondary rays of light transport paths in a virtual environment to share lighting contributions when determining lighting conditions for a light transport path. Interactions may be shared based on similarities in characteristics (e.g., hit locations), which may define a region in which interactions may share lighting condition data. The region may correspond to a texel of a texture map and lighting contribution data for interactions may be accumulated to the texel spatially and / or temporally, then used to compute composite lighting contribution data that estimates radiance at an interaction. Approaches are also provided for reprojecting lighting contributions of interactions to pixels to share lighting contribution data from secondary bounces of light transport paths while avoiding potential over blurring.

The invention relates to a method, a device and equipment for synchronously adjusting global illumination brightness of a train and a medium. The method comprises the following steps: acquiring a plurality of illumination data of a first train and a tail train of the train; performing data verification on the illumination data to remove corresponding abnormal data, and calculating the illumination data after the abnormal data is removed through dynamic weighting to obtain a current average illumination value; based on the current average illumination value, obtaining an illumination change trend in a preset time period through a preset illumination prediction model; generating an illumination adjustment instruction according to the illumination change trend, and synchronously issuing the illumination adjustment instruction to each compartment through a ring topology network; and calling a local dynamic gradient dimming algorithm to generate dimming control parameters based on the illumination adjustment instruction, and further controlling the illumination equipment to execute brightness adjustment operation. The method has the effect of reducing the brightness difference of the train carriages.

The invention discloses a global neural drawing method and system oriented to hybrid representation optimization, and belongs to the technical field of computer graphics, and the method comprises the steps: dividing a screen into a plurality of tiles, and obtaining a first workload index on each tile in a first drawing stage and a second workload index on each tile in a second drawing stage; generating a cross-tile and cross-stage unified scheduling queue based on the first workload index and the second workload index, and executing the drawing tasks on different tiles in parallel according to the unified scheduling queue; and triggering a subsequent feature fusion and neural global illumination drawing stage when the inter-stage dependency condition is met so as to generate an output image with a global illumination effect. According to the method, the end-to-end frame rate oriented to the modern AI accelerator / AI-GPU can be remarkably improved and the tail delay can be reduced on the premise of ensuring the visual quality and the time sequence stability, and the method is suitable for application scenes such as real-time global illumination, large-scale complex scene drawing and interactive neural rendering.

The invention relates to an intelligent super-lens light field camera circuit board detection method based on deep reinforcement learning. The method comprises the following steps: constructing a circuit board detection model of an intelligent super-lens light field camera; obtaining illumination parameters of the surface of the circuit board by using the real-time global illumination model; accurately positioning the circuit board by using a dense optical flow method to obtain a refocusing parameter of the light field image; a depth parameter of a light field image is obtained by using a light field layer-by-layer scanning technology and a photoelectric intelligent frequency multiplexing modulation technology; constructing a 5D light field model of the intelligent super-lens light field camera, and obtaining a 5D light field image of the circuit board; and constructing a space-time angle deep reinforcement learning model based on multiple agents, inputting the obtained illumination parameters, the refocusing parameters, the depth parameters and the 5D light field image into the space-time angle deep reinforcement learning model, and outputting collaborative decision control of multi-agent optimization. The intelligent super-lens light field camera opens up a new idea for accurate and intelligent detection of circuit board defects.

The invention provides an unmanned aerial vehicle target detection method and device based on infrared and visible light image fusion, and the method comprises the steps: collecting images of two modes of a same scene at the same time through a sensor carried on an unmanned aerial vehicle, and extracting global illumination information from a visible light image to generate an illumination weight, calculating weighting coefficients of the two modes according to the illumination weight; weighting the visible light feature map and the infrared feature map by using corresponding weighting coefficients to obtain weighted features; determining a frequency domain difference between the weighted features of the two modes, and enhancing the weighted features according to the frequency domain difference to obtain enhanced features; splicing the enhanced features of the two modes, respectively inputting a global branch and a local branch, obtaining a global offset field and a local offset field, superposing the global offset field and the local offset field to obtain a final offset field, and aligning the implicit positions of the infrared enhanced features by using the final offset field; and splicing the aligned enhanced features of the two modalities, and inputting the spliced enhanced features into a target detection head to obtain a target detection result. According to the invention, the target detection precision and robustness are improved.

The invention provides a global illumination rendering method and device, electronic equipment and a storage medium. The method comprises the steps that scene data are acquired, and the scene data comprise data needed by baking of an illumination probe and an auxiliary point preset in a scene; baking the scene according to the scene data to obtain a baking result; wherein the baking result comprises brightness baking results of the illumination probe and the auxiliary point, and spherical harmonic coefficient data of the illumination probe; according to the brightness baking results of the illumination probe and the auxiliary point, predicting internal and external information of the illumination probe relative to the target light source, and obtaining target internal and external information of the illumination probe; and when the scene is rendered, performing global illumination calculation of the object according to the target internal and external information and the spherical harmonic coefficient data of the illumination probe. The problem of internal and external light leakage of the illumination probe can be automatically solved, and meanwhile, the storage data volume, the operation overhead and the labor cost are balanced.