Abstract: A method and apparatus for liveness detection includes: processing a target image to obtain probabilities of multiple pixel points of the target image to be corresponding to spoofing; determining a predicted face region in the target image; and obtaining, based on the probabilities of the multiple pixel points of the target image to be corresponding to spoofing and the predicted face region, a liveness detection result of the target image.

Abstract: An analysis method of coal consumption of the thermal power unit during peak shaving transients includes measuring and recording the coal-feeding rate under different steady-state loads, and then establishing the relationship between the coal-feeding rate and the load, wherein the coal consumption index of the unit during transients can be directly presented by the difference between the real-time coal-feeding rate and a steady-state corresponding value; the total coal increment can be obtained by integrating the real-time coal-feeding rate increment with time; for different loads, the coal consumption increment due to the unit's thermal storage variation can be defined as the thermal storage coal consumption increment; the thermal storage deviation of the unit during transients causes the additional coal consumption, which is defined as the process control coal consumption increment. This work can provide the clear guidance for the fuel control of the thermal power unit during peak shaving processes.

Abstract: A 3D object detection method includes: obtaining two-dimensional (2D) coordinates of at least one predetermined key point of a target object in an image to be processed; constructing a pseudo 3D detection body of the target object in a 2D space according to the 2D coordinates of the at least one predetermined key point; obtaining depth information of a plurality of vertices of the pseudo 3D detection body; and determining a 3D detection body of the target object in a 3D space according to the depth information of the plurality of vertices of the pseudo 3D detection body.

Abstract: An analysis method of coal consumption of the thermal power unit during peak shaving transients includes measuring and recording the coal-feeding rate under different steady-state loads, and then establishing the relationship between the coal-feeding rate and the load, wherein the coal consumption index of the unit during transients can be directly presented by the difference between the real-time coal-feeding rate and a steady-state corresponding value; the total coal increment can be obtained by integrating the real-time coal-feeding rate increment with time; for different loads, the coal consumption increment due to the unit's thermal storage variation can be defined as the thermal storage coal consumption increment; the thermal storage deviation of the unit during transients causes the additional coal consumption, which is defined as the process control coal consumption increment. This work can provide the clear guidance for the fuel control of the thermal power unit during peak shaving processes.

Abstract: The present disclosure discloses a camera optical lens. The camera optical lens includes, in an order from an object side to an image side, a first lens, an aperture, a second lens, a third lens, a fourth lens, and a fifth lens. The camera optical lens further satisfies specific conditions.

Abstract: A method for anti-spoofing detection includes: obtaining at least one image subsequence from an image sequence, where the image sequence is acquired by an image acquisition apparatus after prompting a user to read a specified content, and the image subsequence includes at least one image in the image sequence; performing lipreading on the at least one image subsequence to obtain a lipreading result of the at least one image subsequence; and determining an anti-spoofing detection result based on the lipreading result of the at least one image subsequence.

Abstract: The present disclosure relates to the field of optical lenses and provides a camera optical lens. The camera optical lens includes, from an object side to an image side: an aperture; a first lens having a positive refractive power; a second lens having a negative refractive power; a third lens having a positive refractive power; a fourth lens having a negative refractive power; a fifth lens having a negative refractive power; a sixth lens having a positive refractive power; and a seventh lens having a negative refractive power. The camera optical lens satisfies following conditions: 3.00?v1/v2?4.20; and ?21.00?f2/f1??5.00, where f1 denotes a focal length of the first lens; f2 denotes a focal length of the second lens; v1 denotes an abbe number of the first lens; and v2 denotes an abbe number of the second lens.

Abstract: A face unlocking method includes: performing face detection on one or more images; performing face feature extraction on an image in which a face is detected; performing authentication on extracted face features based on stored face features, wherein the stored face features at least comprise face features of face images of at least two different angles corresponding to a same identity (ID); and performing an unlocking operation at least in response to the extracted face features passing the authentication.

Abstract: The present disclosure provides a glass lens and a lens module. The glass lens has an optical axis, and includes an optical portion and a connecting portion surrounding the optical portion. The connecting portion includes a first reference surface and a second reference surface opposite to the first reference surface. The optical portion includes a first optical surface located on one side of the first reference surface and a second optical surface located on one side of the second reference surface. The structure of the glass lens of the present disclosure can form a smaller optical portion without occupying space, and meanwhile, a matching structure can be disposed on the second reference surface of the connecting portion, which can effectively reduce the installation difficulty and positioning cost of the glass lens, and make the product have excellent optical performances meanwhile.

Abstract: A method for object detection includes: obtaining a plurality of to-be-determined targets in a to-be-detected image; determining confidences of the plurality of to-be-determined targets separately belonging to at least one category, determining categories of the plurality of to-be-determined targets according to the confidences, and determining position offset values corresponding to the respective categories of the plurality of to-be-determined targets; using the position offset values corresponding to the respective categories of the plurality of to-be-determined targets as position offset values of the plurality of to-be-determined targets; and determining position information and a category of at least one to-be-determined target in the to-be-detected image according to the categories of the plurality of to-be-determined targets, the position offset values of the plurality of to-be-determined targets, and the confidences of the plurality of to-be-determined targets belonging to the categories thereof.

Abstract: A target object recognition method includes: performing target object detection on an object of an image to be detected to obtain target object prediction information of the object, where the target object prediction information is confidence information that the detected object is the target object; performing key point detection on the object of the image to be detected to obtain key point prediction information of the object, where the key point prediction information is confidence information that a key point of the detected object is a key point of the target object; fusing the target object prediction information with the key point prediction information to obtain comprehensive prediction information of the object; and recognizing the target object according to the comprehensive prediction information.

Abstract: Embodiments of the present application disclose methods and apparatuses for determining a bounding box of a target object, media, and devices. The method includes: obtaining attribute information of each of a plurality of key points of a target object; and determining a bounding box position of the target object according to the attribute information of each of the plurality of key points of the target object and to a preset neural network. The implementations of the present application can improve the efficiency and accuracy of determining a bounding box of a target object.

Abstract: Embodiments of the present disclosure provide methods and apparatuses for vehicle appearance feature recognition, methods and apparatuses for vehicle retrieval, storage media, and electronic devices. The method for vehicle appearance feature recognition includes: obtaining multiple region segmentation results of a target vehicle from an image to be recognized; extracting global feature data and multiple pieces of region feature data from the image to be recognized based on the multiple region segmentation results; and fusing the global feature data and the multiple pieces of region feature data to obtain appearance feature data of the target vehicle.

Abstract: A vehicle lamp detection method includes: obtaining an image block including an image of a vehicle; and performing vehicle lamp detection on the image block by means of a deep neural network, to obtain a vehicle lamp detection result.

Abstract: Methods, apparatuses, devices, program products, and media can improve the accuracy rate of searching for a target person. The method includes: obtaining an image of the target person; searching a face image library by using the image of the target person to obtain a first face image template matching the image of the target person, where the face image library includes a plurality of face image templates; and obtaining, according to the first face image template and a pedestrian image library, at least one target pedestrian image template matching the image of the target person, where the pedestrian image library includes a plurality of pedestrian image templates.

Abstract: The present disclosure discloses a camera optical lens. The camera optical lens including, in an order from an object side to an image side, a first lens, a second lens, a third lens, a fourth lens, a fifth lens, a sixth lens and a seventh lens. The camera optical lens further satisfies specific conditions.

Abstract: Methods, apparatuses and electronic devices for identifying an object category include: determining M key point neighborhood regions from corresponding object candidate boxes according to position information of M key points in a plurality of object candidate boxes of an image to be detected, where M is less than or equal to the total number of key points of N preset object categories, and M and N are positive integers; and determining category information of at least one object in the image to be detected using a convolutional neural network model used for identifying an object category in the image according to the M key point neighborhood regions.

Abstract: A method and an apparatus for detecting an object keypoint, an electronic device, a computer readable storage medium, and a computer program include: obtaining a respective feature map of at least one local regional proposal box of an image to be detected, the at least one local regional proposal box corresponding to at least one target object; and separately performing target object keypoint detection on a corresponding local regional proposal box of the image to be detected according to the feature map of the at least one local regional proposal box.

Abstract: The present disclosure discloses a camera optical lens. The camera optical lens includes, in an order from an object side to an image side, a first lens, an aperture, a second lens, a third lens, a fourth lens, and a fifth lens. The camera optical lens further satisfies specific conditions.

Abstract: The present disclosure discloses a camera optical lens. The camera optical lens including, in an order from an object side to an image side, a first lens, a second lens, a third lens, a fourth lens, a fifth lens, a sixth lens and a seventh lens. The camera optical lens further satisfies specific conditions.