Abstract: A face image retrieval method includes: obtaining to-be-retrieved face information corresponding to a to-be-retrieved image by a convolutional neural network, the convolutional neural network being configured with corresponding convolution calculation configuration information by a processor, the convolutional neural network including at least one convolutional layer, the convolution calculation configuration information including a data bit width value corresponding to each convolutional layer in the convolutional neural network, and the to-be-retrieved image including at least one face region; searching a database for matched preset face image information that matches the to-be-retrieved face information, the database storing at least one piece of preset face image information; and outputting the preset face image information that matches the to-be-retrieved face information.

Abstract: Methods and apparatuses for detecting a face, and electronic devices include: performing face location on a face image to be detected; performing face attribute detection on the face image based on a face location result; and displaying a face attribute detection result of the face image to be detected. Use experience of face image detection can be improved while diversified requirements of a user for obtaining corresponding face information in a face image from different angles are satisfied.

Abstract: A methods for determining face image quality includes: obtaining pose angle information and/or size information of a face in an image; and obtaining quality information of the face in the image on the basis of the pose angle information and/or the size information of the face.

Abstract: A video processing method includes: a convolution parameter corresponding to a frame to be processed in a video sequence is acquired, the convolution parameter including a sampling point of a deformable convolution kernel and a weight of the sampling point; and denoising processing is performed on the frame to be processed based on the sampling point of the deformable convolution kernel and the weight of the sampling point to obtain a denoised video frame.

Abstract: A face recognition device includes a screen component, a middle frame and a radio frequency antenna. The screen component is installed on the middle frame, the radio frequency antenna is disposed between the middle frame and the screen component, and the screen component is provided with a clear zone, so that the radio frequency antenna radiates electromagnetic waves outward through the clear zone of the screen component. Since the radio frequency antenna is disposed between the middle frame and the screen component and the screen component is provided with the clear zone, the radio frequency antenna can radiate electromagnetic waves outward through the clear zone on the screen component, so as to establish a communication with an electronic tag.

Abstract: An access control method, an access control apparatus, a system, and a storage medium are disclosed. The method includes: acquiring a scene image, and recognizing one or more face images in the scene image; determining an attribute of the face image, the attribute including a registered user and an unregistered user; and if multiple face images are recognized, determining whether attributes corresponding to the multiple face images include the registered user, and responsive to determining that the attributes corresponding to the multiple face images comprise the registered user, controlling an access control device to be opened; responsive to determining that the attributes corresponding to the multiple face images does not comprise the registered user, in condition that an access control verification request instruction is received and verification for the access control verification request instruction succeeds, controlling the access control device to be opened.

Abstract: The present disclosure relates to a data processing method and apparatus, and a storage medium. The method includes: inputting input data into a neural network model to obtain feature data currently output by a network layer in the neural network model (S100); determining, according to transformation parameters of the neural network model, a normalization mode matched with the feature data (S200), wherein the transformation parameters are used for adjusting a statistical range of statistics of the feature data, and the statistical range is used for representing the normalization mode; and performing normalization processing on the feature data according to the determined normalization mode to obtain normalized feature data (S300). According to embodiments of the present disclosure, the purpose of autonomously learning a matched normalization mode for each normalization layer of the neural network model can be implemented without human intervention.

Abstract: An image processing method includes: obtaining an original photographed image and original depth information of at least one pixel point in the original photographed image; determining blurring degree data of each of the at least one pixel point in the original photographed image according to blurring parameter data and the original depth information of the at least one pixel point; and performing blurring processing on the original photographed image according to the blurring degree data of the at least one pixel point to generate a post-processing result image.

Abstract: A face image processing method includes: performing face detection on a to-be-processed image, to obtain at least one face region image included in the to-be-processed image and face key point information in the at least one face region image; and processing, for the at least one face region image, an image corresponding to a first region and/or an image corresponding to a second region in the face region image at least according to the face key point information in the face region image, wherein the image corresponding to the second region and the image corresponding to the first region are at least partially non-overlapping.

Abstract: An image acquisition device includes: a main body structure provided with an image acquisition means and at least two accommodating structures, the at least two accommodating structures including a first accommodating structure configured to place a first target object and a second accommodating structure configured to place a second target object, where the first accommodating structure is arranged at a first position of the main body structure, the first position satisfying the condition that the first target object placed on the first accommodating structure is located within acquisition area coverage of the image acquisition means; and the second accommodating structure is arranged at a second position of the main body structure, the second position satisfying the condition that the second target object placed on the second accommodating structure is located within the acquisition area coverage of the image acquisition means.

Abstract: A neural network training method and apparatus and an image matching method and apparatus are provided. The neural network training method at least includes: labeling annotation information of a first clothing instance and a second clothing instance, where the first clothing instance and the second clothing instance are respectively from a first clothing image and a second clothing image; pairing the first clothing image and the second clothing image in response to a state of matching between the first clothing instance and the second clothing instance; and training a neural network to be trained based on the paired first clothing image and second clothing image.

Abstract: A method and an apparatus for identity verification, an electronic device, a computer program, and a storage medium include: obtaining a first image of a document, where the first image contains a first face image; obtaining a second image containing a face of a to-be-verified person; performing face comparison on the first image and the second image to obtain a first comparison result; and obtaining an identity verification result according to the first comparison result.

Abstract: Embodiments of the application disclose a road marking recognition method, a map generation method, and related products. The road marking recognition method includes that: a base map of a road is determined according to acquired point cloud data of the road, pixels in the base map being determined according to reflectivity information of an acquired point cloud and position information of the point cloud; a pixel set composed of the pixels in the base map that road markings include is determined according to the base map; and at least one road marking is determined according to the determined pixel.

Abstract: A method for detecting a blocking state of an image acquisition device, an electronic device, and a computer storage medium are provided. The method includes: an image acquired by an image acquisition device is obtained; and it is determined, according to the acquired image, whether the image acquisition device is in a blocked state.

Abstract: A method and an apparatus for verifying an identity document, an electronic device, and a storage medium include: collecting an identity document image of a current identity document by means of a first camera; recognizing characters in the identity document image to obtain first identity document data; obtaining second identity document data of the identity document by means of an identity document reader; and verifying authenticity of the identity document according to the first identity document data and the second identity document data.

Abstract: An image acquisition device includes a main body and a camera. A rotating portion is provided on the main body. The camera is arranged on the rotating portion. A knob portion is provided on the rotating portion at a lateral side of the camera in the axial direction. The knob portion can drive the rotating portion to rotate.

Abstract: The present disclosure relates to a method and apparatus for detecting a state of a signal indicator light, and a method and apparatus for driving control. The method for detecting a state of a signal indicator light includes: detecting a target region in a target image and determining first feature values of pixels within the target region, where at least one signal indicator light having different display states is present in the target region; clustering the pixels within the target region based on the first feature values to obtain a plurality of class groups for the pixels; and determining a display state of the signal indicator light based on the obtained plurality of class groups.

Abstract: Image blurring methods and apparatuses, storage media, and electronic devices. The method can be carried out by the apparatuses, media and devices, and includes: generating a second image having second pixel points corresponding to first pixel points of a first image; determining, according to blurring desired data of the first pixel points, respective initial blurring weight values of the corresponding second pixel points; performing at least one update on at least one of the second pixel points, the update including: updating, based on a first pixel value of the first pixel point and a current blurring weight value of the second pixel point corresponding to the based first pixel point, a current pixel value and a current blurring weight value of at least one neighboring second pixel point of the based corresponding second pixel point; and obtaining a blurring result of the first image according to the updated second image.

Abstract: An image processing method includes: obtaining a facial skin tone area in an image to be processed; filtering the image to be processed to obtain a filtered smooth image; obtaining a high-frequency image based on the smooth image and the image to be processed; obtaining a facial skin tone high-frequency image based on the high-frequency image and a facial skin tone mask; and superimposing the high-frequency image and the image to be processed based on the facial skin tone mask and preset first superimposition strength in a luma channel, and superimposing a luma channel signal of the facial skin tone high-frequency image onto a luma channel signal of the image to be processed, to obtain a first image.

Abstract: Image blurring methods and apparatuses, storage media, and electronic devices can include: obtaining a main image and a secondary image obtained by photographing the same object with a dual-lens camera; obtaining depth data and depth confidence degree data according to the main image and the secondary image, the depth data indicating depth values of corresponding pixel points in the main image and the secondary image, and the depth confidence degree data indicating confidence degrees of the depth values in the depth data; correcting at least one depth value in the depth data according to the depth confidence degree data; and blurring the main image according to corrected depth data.