Abstract: The embodiments of the present disclosure disclose image defogging method. A specific mode of carrying out the method includes the steps to: obtain a polarized fog-free scene image set, generate a first quintuple based on each polarized fog-free scene image, and obtain a first quintuple set; extract pixel coordinates meeting a preset condition from the significant polarization image included in each first quintuple, to obtain a pixel coordinate group to generate a second quintuple; generate a simulated polarization foggy scene image sequence based on each second quintuple, to obtain a simulated polarization foggy scene data set; design a polarization state attention neural network; obtain a polarized foggy scene image, and input the polarized foggy scene image into the polarization state attention neural network to obtain a polarized defogging image. This embodiment can still improve the accuracy of image defogging with poor lighting conditions.

Abstract: The embodiments of the present disclosure disclose method for calculating image highlight reflection separation. A specific implementation of the method includes: controlling a polarized color sensor to shoot a polarized color image, and calculating a polarized chromaticity image; clustering the pixels of diffuse reflection components whose chromaticity difference is within a preset range, to obtain a pixel sequence set; using a robust principal component analysis algorithm for each pixel, to obtain an initial separation result; further processing the polarized color image for highlight reflection separation, to obtain a highlight reflection separation result, and generating a diffuse reflection image. This implementation can achieve highlight reflection separation for images without being affected by the lighting information, and obtain a highlight reflection separation result with higher accuracy through the color and polarization information.

Abstract: The present application provides a display device including a display panel; a back plate disposed on an opposite side of the light-exiting surface of the display panel; an intermediate support member disposed on a side of the back plate away from the display panel; and a conductor support member disposed on a side of the intermediate support member away from the back plate, wherein the intermediate support member is provided with an opening, and a conductive member is disposed in the opening, and wherein opposite ends of the first conductive member are in electrical contact with the conductive layer and the conductive member, respectively.

Abstract: The embodiments of the present disclosure disclose method for calculating image highlight reflection separation. A specific implementation of the method includes: controlling a polarized color sensor to shoot a polarized color image, and calculating a polarized chromaticity image; clustering the pixels of diffuse reflection components whose chromaticity difference is within a preset range, to obtain a pixel sequence set; using a robust principal component analysis algorithm for each pixel, to obtain an initial separation result; further processing the polarized color image for highlight reflection separation, to obtain a highlight reflection separation result, and generating a diffuse reflection image. This implementation can achieve highlight reflection separation for images without being affected by the lighting information, and obtain a highlight reflection separation result with higher accuracy through the color and polarization information.

Abstract: The embodiments of the present disclosure disclose image defogging method. A specific mode of carrying out the method includes the steps to: obtain a polarized fog-free scene image set, generate a first quintuple based on each polarized fog-free scene image, and obtain a first quintuple set; extract pixel coordinates meeting a preset condition from the significant polarization image included in each first quintuple, to obtain a pixel coordinate group to generate a second quintuple; generate a simulated polarization foggy scene image sequence based on each second quintuple, to obtain a simulated polarization foggy scene data set; design a polarization state attention neural network; obtain a polarized foggy scene image, and input the polarized foggy scene image into the polarization state attention neural network to obtain a polarized defogging image. This embodiment can still improve the accuracy of image defogging with poor lighting conditions.

Abstract: Disclosed are a method and apparatus for adaptively constructing a three-dimensional indoor scenario, the method including: establishing an object association map corresponding to different scenario categories according to an annotated indoor layout; selecting a corresponding target indoor object according to room information inputted by a user and the object association map; generating a target indoor layout according to preset room parameters inputted by the user and the annotated indoor layout; and constructing a three-dimensional indoor scenario according to the target indoor object and the target indoor layout. The disclosed method and apparatus help improving the efficiency in constructing the three-dimensional scenario.

Abstract: The disclosed provides a posture-guided cross-category method and device for combination modeling of cross-category 3D models, the method including: receiving a first posture model inputted by a user; calculating similarities between q first regions of the first posture model and q second regions of each of second posture models in a preset model database, respectively; where the model database includes a plurality of models partitioned into model components, and second posture models corresponding to the models; where the q first regions correspond to the q second regions one on one, where q is an integer greater than or equal to 2; selecting a corresponding plurality of model components of the q second regions of the second posture model according to the similarities; and combining the selected plurality of model components to generate a 3D model. The embodiment of the present application can combine cross-category models with large structural differences.

Abstract: Disclosed are a method and apparatus for adaptively constructing a three-dimensional indoor scenario, the method including: establishing an object association map corresponding to different scenario categories according to an annotated indoor layout; selecting a corresponding target indoor object according to room information inputted by a user and the object association map; generating a target indoor layout according to preset room parameters inputted by the user and the annotated indoor layout; and constructing a three-dimensional indoor scenario according to the target indoor object and the target indoor layout. The disclosed method and apparatus help improving the efficiency in constructing the three-dimensional scenario.

Abstract: The disclosed provides a posture-guided cross-category method and device for combination modeling of cross-category 3D models, the method including: receiving a first posture model inputted by a user; calculating similarities between q first regions of the first posture model and q second regions of each of second posture models in a preset model database, respectively; where the model database includes a plurality of models partitioned into model components, and second posture models corresponding to the models; where the q first regions correspond to the q second regions one on one, where q is an integer greater than or equal to 2; selecting a corresponding plurality of model components of the q second regions of the second posture model according to the similarities; and combining the selected plurality of model components to generate a 3D model. The embodiment of the present application can combine cross-category models with large structural differences.