International Business Machines Corporation

Samsung Electronics Co., Ltd.

Beijing Zitiao Network Technology Co., Ltd.

Hao Feng

Chao Zhang

Shuo Li

Jingtao Xu

ShengYan Sun

Changkyu Choi

Jae-Joon Han

Yanhu Shan

Xin Yang

Biao Wang

Yaozu An

Jaejoon Han

Sheng Yan Sun

Byungin Yoo

Ming Wang

Youngjun Kwak

Youngsung Kim

Wonjun Hwang

Deheng Qian

Wonsuk Chang

Xuetao Feng

Hongwei Zhang

Lujin Gong

Chang Kyu Choi

Bing Yu

Jungbae Kim

Sungjoo Suh

Hui Jiang

The present disclosure provides a method and apparatus for processing resources. The method comprises: in response to a trigger operation for supplementing first virtual resources, determining a current remaining resource amount of second virtual resources; then, when the remaining resource amount of the second virtual resources meets preset conditions, determining the consumption amount of the second virtual resources according to a resource amount conversion relationship between the first virtual resources and the second virtual resources, and the amount of the first virtual resources to be supplemented; and finally, according to the consumption amount of the second virtual resources and the amount of the first virtual resources to be supplemented, updating the remaining resource amounts of the first virtual resources and the second virtual resources. The embodiments of the present disclosure improve the fluency and continuity of a user operation, and simplify steps for supplementing the first virtual resources.

Method and apparatus for processing resources

An image processing method implemented by a processor includes receiving an image, acquiring a target image that includes an object from the image, calculating an evaluation score by evaluating a quality of the target image, and detecting the object from the target image based on the evaluation score.

Image processing method and apparatus for object detection

A liveness test method and apparatus is disclosed. The liveness test method includes detecting a face region in an input image for a test target, implementing a first liveness test to determine a first liveness value based on a first image corresponding to the detected face region, implementing a second liveness test to determine a second liveness value based on a second image corresponding to a partial face region of the detected face region, implementing a third liveness test to determine a third liveness value based on an entirety of the input image or a full region of the input image that includes the detected face region and a region beyond the detected face region, and determining a result of the liveness test based on the first liveness value, the second liveness value, and the third liveness value.

Liveness test method and apparatus

A method of detecting a target includes generating an image pyramid based on an image on which a detection is to be performed; classifying candidate areas in the image pyramid using a cascade neural network; and determining a target area corresponding to a target included in the image based on the plurality of candidate areas, wherein the cascade neural network includes a plurality of neural networks, and at least one neural network among the neural networks includes parallel sub-neural networks.

Target detection method and apparatus

Techniques are provided for evaluating the security of data access statements. Specifically, in one embodiment of the claimed subject matter there is provided a technique for evaluating the security of data access statements, comprising: evaluating the criticality of multiple SQL statements contained in multiple sessions accessing a database; generating a critical item set from the multiple sessions, each element in the critical item set indicating one or more SQL statements contained in a session; extracting at least one association rule from the critical item set, each of the at least association rule indicating a sequence of SQL statements contained in a session; and calculating the criticality of each of the at least one association rule.

Evaluating security of data access statements

Disclosed is a liveness test method and apparatus. A liveness test apparatus determines a pre-liveness score based on a plurality of sub-images acquired from an input image, determines a post-liveness score based on a recognition model for recognizing an object included in the input image, and determines a liveness of the object based on any one or any combination of the pre-liveness score and the post-liveness score.

In an embodiment of the present invention, a command for performing a database operation with respect to a table of a database is received, whereby the table has a visible key column for identification information and one or more invisible token columns for token information. The user's role from the command is obtained. A record is identified in the table based on a combination of the identification information and the token information corresponding to the user's role. The database operation is performed on the identified record.

Access control for database

A processor implemented image processing method includes acquiring a facial image by performing a face detection on an image, performing a quality assessment on the facial image using a preset facial image regression model, and determining a quality level of the facial image based on the quality assessment.

Apparatus and method for image processing

Disclosed is a face detection method and apparatus, the method including detecting a candidate area from a target image using a first sliding window moving at an interval of a first step length and detecting a face area in the candidate area using a second sliding window moving at an interval of a second step length less than the first step length.

Face detection method and apparatus

Provided is a 3D registration method and apparatus that may select a key point from among plural points included in 3D target data, based on a geometric feature or a color feature of each of the plural points, may adjust a position of the selected key point of the 3D target data based on features of, or a distance between, a key point of the 3D source data and the selected key point of the 3D target data, may calculate reliabilities of plural key points of the 3D source data based on respective features of at least one key point of the 3D target data determined to correspond to the plural key points of the 3D source data, and may generate 3D registration data by performing 3D registration between the 3D source data and the 3D target data based on the calculated reliabilities.

Registration method and apparatus for 3D image data

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Beijing, China

Hao Feng