Abstract: The disclosure discloses a high-viscosity, high-elasticity, and anti-aging composite modified asphalt and a preparation method thereof, belongs to the technical field of road engineering materials, and solves the technical problem that the comprehensive performance of an existing asphalt ultrathin wearing layer needs to be further improved so as to prolong the service life of a pavement surface layer and reduce the pavement maintenance costs. The composite modified asphalt is prepared from the following components in parts by mass: 100 parts of a matrix asphalt, 10 to 15 parts of a thermoplastic styrene-butadiene rubber, 5 to 8 parts of a tackifier, 0.5 to 1.5 parts of a plasticizer, 2 to 5 parts of a compatibilizer, 0.1 to 0.4 parts of a stabilizer, and 0.01 to 0.05 parts of an anti-aging agent. The composite modified asphalt prepared by the disclosure has the advantages of high elasticity, high viscosity, excellent aging resistance, etc.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately and flexibly generating harmonized digital images utilizing an object-to-object harmonization neural network. For example, the disclosed systems implement, and learn parameters for, an object-to-object harmonization neural network to combine a style code from a reference object with features extracted from a target object. Indeed, the disclosed systems extract a style code from a reference object utilizing a style encoder neural network. In addition, the disclosed systems generate a harmonized target object by applying the style code of the reference object to a target object utilizing an object-to-object harmonization neural network.

Abstract: Aspects relate to techniques for efficient sidelink resource reservation based on the congestion on a sidelink. A wireless communication device may transmit control information indicating a number of resources reserved for an initial transmission and at least one retransmission of a packet. In some examples, the number of resources included in the control information can be either three resources or two resources based on the congestion. For example, the number of resources included in the control information can be three resources in response to a congestion value representing the congestion on the sidelink being less than a threshold. In addition, the number of resources included in the control information can be two resources in response to the congestion value being greater than or equal to the threshold.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for training and/or implementing machine learning models utilizing compressed log scene measurement maps. For example, the disclosed system generates compressed log scene measurement maps by converting scene measurement maps to compressed log scene measurement maps by applying a logarithmic function. In particular, the disclosed system uses scene measurement distribution metrics from a digital image to determine a base for the logarithmic function. In this way, the compressed log scene measurement maps normalize ranges within a digital image and accurately differentiates between scene elements objects at a variety of depths. Moreover, for training, the disclosed system generates a predicted scene measurement map via a machine learning model and compares the predicted scene measurement map with a compressed log ground truth map.

Abstract: An image processing system obtains an input image (e.g., a user provided image, etc.) and a mask indicating an edit region of the image. A user selects an image editing mode for an image generation network from a plurality of image editing modes. The image generation network generates an output image using the input image, the mask, and the image editing mode.

Abstract: Techniques are disclosed for automatic sky replacement with edge lighting enhancements. A method of automatic sky replacement includes generating a clean mask and a compositing mask for an input image using a mask generation network. A plurality of layers is generated using the clean mask and the compositing mask. The plurality of layers includes an edge lighting layer generated based on a subset of the plurality of layers and the clean mask. A composite image is generated by combining the input image and the plurality of layers including the edge lighting layer.

Abstract: A computing device can receive a query that identifies a set of data to be processed and determine that a portion of the set of data resides in an external data system. The query system can request data identifiers associated with data objects of the set of data from the external data system and communicate the data identifiers to a data queue. The computing device can instruct one or more search nodes to retrieve the identifiers from the data queue. The search nodes can use the data identifiers to retrieve data objects from the external data system and process the data objects according to instructions received from the computing device. The search nodes can provide results of the processing to the computing device.

Abstract: In some embodiments, an application receives a request to execute a convolutional neural network model. The application determines the computational complexity requirement for the neural network based on the computing resource available on the device. The application further determines the architecture of the convolutional neural network model by determining the locations of down-sampling layers within the convolutional neural network model based on the computational complexity requirement. The application reconfigures the architecture of the convolutional neural network model by moving the down-sampling layers to the determined locations and executes the convolutional neural network model to generate output results.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that generates object shadows for digital images utilizing corresponding geometry-aware buffer channels. For instance, in one or more embodiments, the disclosed systems generate, utilizing a height prediction neural network, an object height map for a digital object portrayed in a digital image and a background height map for a background portrayed in the digital image. The disclosed systems also generate, from the digital image, a plurality of geometry-aware buffer channels using the object height map and the background height map. Further, the disclosed systems modify the digital image to include a soft object shadow for the digital object using the plurality of geometry-aware buffer channels.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that generates object shadows for digital images utilizing height maps for the digital objects and background portrayed therein. For instance, in one or more embodiments, the disclosed systems generate, utilizing a height prediction neural network, an object height map comprising pixel heights for pixels of a digital object portrayed in a digital image. The disclosed system also generate, utilizing the height prediction neural network, a background height map comprising additional pixel heights for pixels of a background portrayed in the digital image. Further, the disclosed systems modify the digital image to include an object shadow for the digital object using the object height map and the background height map.

Abstract: In implementations of systems for performing multiple segmentation tasks, a computing device implements a segment system to receive input data describing a digital image depicting an object. The segment system computes per-pixel embeddings for the digital image using a pixel decoder of a machine learning model. Output embeddings are generated using a transformer decoder of the machine learning model based on the per-pixel embeddings for the digital image, input embeddings for a first segmentation task and input embeddings for a second segmentation task. The segment system outputs a first digital image and a second digital image. The first digital image depicts the object segmented based on the first segmentation task and the second digital image depicts the object segmented based on the second segmentation task.

Abstract: A vehicle window assembly and a vehicle are provided. The vehicle window assembly includes a laminated glass, a fixing member, and a connecting member. The laminated glass, as a primary viewing portion of the vehicle window assembly, has a primary viewing direction. The fixing member is integrally formed and defines multiple fixing grooves arranged at intervals. An opening direction of each fixing groove is opposite to the primary viewing direction. Multiple functional assemblies are fixedly mounted in the multiple fixing grooves respectively. The laminated glass is connected to the fixing member through the connecting member. A wavelength of a signal emitted and/or received by each of the multiple functional assemblies ranges from 380 nm to 1650 nm. The fixing member has a transmittance of at least 92% for a signal in a wavelength range of 380 nm-1650 nm incident at an angle of incidence of 0°.

Abstract: A surface normal model is trained to predict normal maps from single images using pair-wise angular losses. A training dataset comprising a training image and a ground truth normal map for the training image is received. To train the surface normal model using the training dataset, a predicted normal map is generated for the training image using the surface normal model. A loss is determined as a function of angular values between pairs of normal vectors for the predicted normal map and corresponding angular values between pairs of normal vectors for the ground truth normal map. The surface normal model is updated based on the loss.

Abstract: This disclosure describes methods, non-transitory computer readable storage media, and systems that utilize color density estimation in a blended boundary region of a digital image to generate an image mask. For example, the disclosed system extracts a foreground region, a background region, and a blended boundary region from a digital image. The disclosed system determines a color histogram—within a color space selected utilizing the foreground region and the background region—for a portion of the background region along an edge of the blended boundary region. Additionally, the disclosed system generates a color density map for the blended boundary region by comparing colors in the blended boundary region to colors in the color histogram of the background band. The disclosed system then generates a final mask for the digital image based on the color density map.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately, efficiently, and flexibly generating harmonized digital images utilizing a self-supervised image harmonization neural network. In particular, the disclosed systems can implement, and learn parameters for, a self-supervised image harmonization neural network to extract content from one digital image (disentangled from its appearance) and appearance from another from another digital image (disentangled from its content). For example, the disclosed systems can utilize a dual data augmentation method to generate diverse triplets for parameter learning (including input digital images, reference digital images, and pseudo ground truth digital images), via cropping a digital image with perturbations using three-dimensional color lookup tables (“LUTs”).

Abstract: A power connector includes an insulating body and a power terminal module. The power terminal module includes a first power terminal and a second power terminal. The first power terminal includes a first elastic arm, a second elastic arm, a first abutting arm and a second abutting arm. The second power terminal includes a third elastic arm, a fourth elastic arm and a space between the third elastic arm and the fourth elastic arm. The first elastic arm and the second elastic arm extend into the space. The first abutting arm abuts against the third elastic arm. The second abutting arm abuts against the fourth elastic arm. As a result, the power connector has greater plugging force and better heat dissipation performance.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing to remove a shadow for an object. For instance, in one or more embodiments, the disclosed systems receive a digital image depicting a scene. The disclosed systems access a shadow mask of the shadow in a first location. Further, the disclosed systems generate the modified digital image without the shadow by generating a fill for the first location that preserves a visible location of the first location. Moreover, the disclosed systems generate the digital image without the shadow for the object by combining the fill with the digital image.

Abstract: Systems and methods for instance segmentation are described. Embodiments include identifying an input image comprising an object that includes a visible region and an occluded region that is concealed in the input image. A mask network generates an instance mask for the input image that indicates the visible region of the object. A diffusion model then generates a segmentation mask for the input image based on the instance mask. The segmentation mask indicates a completed region of the object that includes the visible region and the occluded region.

Abstract: Systems and methods for multi-modal image generation are provided. One or more aspects of the systems and methods includes obtaining a text prompt and layout information indicating a target location for an element of the text prompt within an image to be generated and computing a text feature map including a plurality of values corresponding to the element of the text prompt at pixel locations corresponding to the target location. Then the image is generated based on the text feature map using a diffusion model. The generated image includes the element of the text prompt at the target location.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing to synthesize shadows for object(s). For instance, in one or more embodiments, the disclosed systems receive a digital image depicting a scene. The disclosed systems access an object mask of the object depicting in the digital image. The disclosed systems further combine the object mask, the digital image, and a noise representation to generate a combined representation. Moreover, the disclosed systems generate a shadow for the object from the combined representation and further generates the modified digital image by combining the shadow with the digital image.