Abstract: A camera extrinsic parameter correction method includes acquiring multiple road surface images continuous in time and performing classification to obtain a mutated image and a time-adjacent image corresponding to the mutated image; determining a matching point pair from pixel points of the mutated image and pixel points of the corresponding time-adjacent image and determining a target view angle point pair of the matching point pair in a target view angle; and correcting a camera extrinsic parameter corresponding to the mutated image according to the difference between two target view angle points in the target view angle point pair, where the camera extrinsic parameter is configured for conversion of a pixel point in a current view angle into a pixel point in the target view angle.

Abstract: There is provided a method for cross-regional talent flow intention analysis, an electronic device, and a storage medium, which relates to technical fields such as big data processing and data statistics and analysis. A specific implementation solution involves: constructing a talent flow intention network based on search data in a network within a preset period of time; and performing cross-regional talent flow intention analysis based on the talent flow intention network to obtain a talent flow intention analysis result.

Abstract: A method, apparatus, device, and storage medium for entity linking is disclosed. The method includes: acquiring a target text; determining at least one entity mention included in the target text; determining a candidate entity corresponding to each of the entity mention based on a preset knowledge base; determining a reference text of each of the candidate entity and determining additional feature information of each of the candidate entity; and determining an entity linking result based on the target text, each of the reference text, and each piece of the additional feature information, wherein determining the entity linking result includes determining a probability of linking each of the candidate entity to the entity mention based on a splicing of a first embedding vector and a second embedding vector of the target text and a splicing of a first embedding vector and a second embedding vector of each respective reference text.

Abstract: Embodiments of the present disclosure provide a method and apparatus for generating a background-free image, a device, and a medium. The method may include: determining an image proportion of a target subject in an original image; clipping, in response to the image proportion being less than a preset threshold, a subject region image corresponding to the target subject from the original image; determining a corresponding subject region mask based on the subject region image; and synthesizing the subject region mask and the subject region image to generate a background-free image corresponding to the original image.

Abstract: Embodiments of the present application disclose a vehicle positioning method, an apparatus, an electronic device, a vehicle and a storage medium, and relate to the field of automatic driving technology. A specific implementation includes: obtaining perceptual information of a lane where a vehicle is located, and obtaining high-precision information of the lane from a preset high-precision map, where the perceptual information and the high-precision information both include lane line information, and both include curb information and/or guardrail information; determining matching information of the perceptual information and the high-precision information; generating position information of the vehicle according to the matching information.

Abstract: The present disclosure provides a generalization processing method, apparatus, device and computer storage medium, and relates to technical field of artificial intelligence and specifically to a deep learning technique. A specific implementation solution is: determining a set of candidate queries in a query library that are similar to a requested query in at least one of a literal matching manner, a semantic matching manner and a query rewriting manner; determining a generalized query corresponding to the requested query from the set of candidate queries by using a pre-trained query matching model; wherein the query matching model is obtained by pre-training based on a cross attention model. The generalization for the requested query can be achieved according to the present disclosure.

Abstract: A Method, apparatus, device, and storage media for image processing are provided. The method include: acquiring a set of image sequences, the set of image sequences including a plurality of image sequences; determining a first similarity measurement between image sequences in the set of image sequences; dividing the set of image sequences into one or more subset of image sequences based on a first similarity measurement; and determining, in each subset of image sequences, degrees of correlation between images in one image sequence of the subset of image sequences and images in other image sequences of the subset of image sequences.

Abstract: Embodiments of the present disclosure disclose a method and apparatus for acquiring information. The method may include: acquiring cloud resource use information; comparing the cloud resource use information with a use rate threshold value, to obtain a comparison result; obtaining use state information of a cloud resource corresponding to the cloud resource use information according to the comparison result; and generating cloud resource state information based on the use state information.

Abstract: A method and apparatus for training models in machine translation, an electronic device and a storage medium are disclosed, which relates to the field of natural language processing technologies and the field of deep learning technologies. An implementation includes mining similar target sentences of a group of samples based on a parallel corpus using a machine translation model and a semantic similarity model, and creating a first training sample set; training the machine translation model with the first training sample set; mining a negative sample of each sample in the group of samples based on the parallel corpus using the machine translation model and the semantic similarity model, and creating a second training sample set; and training the semantic similarity model with the second training sample set.

Abstract: The present disclosure provides a landform map building method and apparatus, an electronic device and a readable storage medium, and relates to the field of image processing technologies.

Abstract: Embodiments of the present disclosure provide a method, apparatus, computer device, and storage medium for determining a POI alias. The method may include: acquiring a to-be-processed target POI, and generating a candidate alias list corresponding to the target POI based on a query behavior-associated log matching the target POI; and screening out at least one target alias corresponding to the target POI in the candidate alias list, according to an association relationship between each candidate alias in the candidate alias list and the target POI.

Abstract: The present disclosure provides a method and an apparatus for coding a video, a device and a medium. An estimated quantization parameter of a target picture in a target GOP is determined. An inter-picture change degree of the target GOP is determined. A propagation ratio of a target picture block to a reference picture block in the target picture is determined based on the estimated quantization parameter of the target picture and the inter-picture change degree. The video is coded based on the propagation ratio.

Abstract: A method and an apparatus for generating a route planning model and a storage medium are provided. The method for generating a route planning model includes: obtaining a target route data set associated with a target site; and determining a target route planning model of the target site with a site optimization object corresponding to the target site, based on the target route data set and a first route planning model; wherein the first route planning model is determined based on a set of historical route data through at least a first training, the set of historical route data being associated with a plurality of sites different from the target site and a first training optimization object for the first training corresponding to the plurality of sites.

Abstract: Provided are an application interface implementation method and apparatus in a host platform layer, a device, and a storage medium, which relate to the field of computer technologies. The implementation scheme includes: the host platform layer acquiring description data of a terminal capability interface; parsing the description data to acquire a communication mode of the terminal capability interface; and configuring a corresponding processor according to the communication mode, configuring a corresponding concept mapping relationship according to the communication mode, or configure a corresponding processor and a corresponding concept mapping relationship according to the communication mode to encapsulate a platform layer interface of the terminal capability interface, where the platform layer interface is configured to process data of communication interactions in a process in which a mini program calls the terminal capability interface through the host platform layer.

Abstract: A method and an apparatus for processing a video are provided technology. The method may include: separating a foreground image and a background image from a video frame in the target video stream, in response to acquiring a target video stream; adding a to-be-displayed content at a target display position in the background image to obtain a processed background image; and combining the foreground image and the processed background image to obtain a target video frame. The present disclosure may directly render the to-be-displayed content in the background, so that the content displayed in the background does not block a body in the foreground, such as person.

Abstract: A product recognition method and device, a model training method and device, and an electronic device are provided. The product recognition method includes: obtaining image data of a product; performing defect recognition on the image data based on a first recognition model, to obtain a first recognition result, wherein the first recognition model is configured to recognize a defective product; performing qualification recognition on the image data based on a second recognition model to obtain a second recognition result, wherein the second recognition model is configured to recognize a qualified product; determining a target recognition result of the product based on the first recognition result and the second recognition result.

Abstract: A method for generating a relighted image includes: obtaining a to-be-processed image and a guidance image corresponding to the to-be-processed image; obtaining a first intermediate image consistent with an illumination condition in the guidance image by performing relighting rendering on the to-be-processed image in a time domain based on the guidance image; obtaining a second intermediate image consistent with the illumination condition in the guidance image by performing relighting rendering on the to-be-processed image in a frequency domain based on the guidance image; and obtaining a target relighted image corresponding to the to-be-processed image based on the first intermediate image and the second intermediate image.

Abstract: A video generation method is provided. The video generation method includes: obtaining global semantic information and local semantic information of a text, where the local semantic information corresponds to a text fragment in the text, searching, based on the global semantic information, a database to obtain at least one first data corresponding to the global semantic information; searching, based on the local semantic information, the database to obtain at least one second data corresponding to the local semantic information; obtaining, based on the at least one first data and the at least one second data, a candidate data set; matching, based on a relevancy between each of at least one text fragment and corresponding candidate data in the candidate data set, target data for the at least one text fragment; and generating, based on the target data matched with each of the at least one text fragment, a video.

Abstract: The present disclosure provides a character recognition model training method and apparatus, a character recognition method and apparatus, a device and a medium, relating to the technical field of artificial intelligence, and specifically to the technical fields of deep learning, image processing and computer vision, which can be applied to scenarios such as character detection and recognition technology. The specific implementing solution is: partitioning an untagged training sample into at least two sub-sample images; dividing the at least two sub-sample images into a first training set and a second training set; where the first training set includes a first sub-sample image with a visible attribute, and the second training set includes a second sub-sample image with an invisible attribute; performing self-supervised training on a to-be-trained encoder by taking the second training set as a tag of the first training set, to obtain a target encoder.

Abstract: The present disclosure provides a signal processing method and apparatus, a device, and a storage medium. The method includes: acquiring a signal set to be processed that carries base station information and base station access time; determining a first signal subset that further carries position information in the signal set to be processed; determining position information of a base station of a first type deployed in a subway station according to the base station information and the position information that are carried by the signal of the first signal subset; and determining position information of a base station of a second type deployed in a subway tunnel according to the position information of the base station of the first type, and the base station information and base station access time that are carried by the signal of the signal set to be processed.