Samsung Electronics Co., Ltd.

Snu Rdb Foundation

Minsu Ko

Seungju Han

Jaejoon Han

Chang Kyu Choi

Deoksang Kim

Jihye Kim

Changyong Son

Sungun Park

Jinwoo Son

Jae-Joon Han

Seon Min Rhee

Byung In Yoo

Sungjoo Suh

Hana Lee

Jiwon Baek

Solae Lee

Youngjun Kwak

Youngsung Kim

Jiho Choi

Heewon Kim

Huijin Lee

Wonsuk Chang

Bohyung Han

Ju Hwan Song

Jungbae Kim

Changkyu Choi

Yong-Il Lee

Seong-Jin Park

Seonmin Rhee

Young Chun Ahn

Wissam Baddar

Eunju Cha

A face verification method and apparatus is disclosed. The face verification method includes selecting a current verification mode, from among plural verification modes, to be implemented for the verifying of the face, determining one or more recognizers, from among plural recognizers, based on the selected current verification mode, extracting feature information from information of the face using at least one of the determined one or more recognizers, and indicating whether a verification is successful based on the extracted feature information.

Face verification method and apparatus

Training of a machine learning model is included. An electronic device includes a memory storing a machine learning model including a discriminator model, and a processor configured to extract, from a training image, a first image patch and a second image patch at least partially overlapping the first image patch, extract, from the first image patch, a first feature map based on a layer of the discriminator model, extract, from the second image patch, a second feature map based on the layer, extract a first partial feature map from a projected map that is projected based on the first feature map, and train the discriminator model based on a first objective function value generated based on a second partial feature map and the first partial feature map, wherein the second partial feature map corresponds to a part of the extracted second feature map.

Electronic device and method with machine learning training

Disclosed is an image fusion method and apparatus. The fusion method includes detecting first feature points of an object in a first image frame from the first image frame; transforming the first image frame based on the detected first feature points and predefined reference points to generate a transformed first image frame; detecting second feature points of the object in a second image frame from the second image frame; transforming the second image frame based on the detected second feature points and the predefined reference points to generate a transformed second image frame; and generating a combined image by combining the transformed first image frame and the transformed second image frame.

Method and apparatus with image fusion

A processor-implemented method includes: generating a first sample image and a second sample image by performing data augmentation on an input training image; generating a first feature map of the first sample image and a second feature map of the second sample image by performing feature extraction on the first sample image and the second sample image using an encoding model; determining first loss data according to a relationship between first feature vectors of the first feature map and second feature vectors of the second feature map; estimating relative geometric information of the first feature map and the second feature map using a relationship estimation model; determining second loss data according to the relative geometric information, based on label data according to a geometric arrangement of the first sample image and the second sample image in the input training image; and training the encoding model and the relationship estimation model, based on the first loss data and the second loss data.

Method and apparatus with recognition model training

A facial verification method and apparatus is disclosed. The facial verification method includes detecting a face region in an input image, determining whether the detected face region represents a partial face, in response to a determination that the detected face region represents the partial face, generating a synthesized image by combining image information of the detected face region and reference image information, performing a verification operation with respect to the synthesized image and predetermined first registration information, and indicating whether facial verification of the input image is successful based on a result of the performed verification operation.

Facial verification method and apparatus

An authentication method and apparatus using a transformation model are disclosed. The authentication method includes generating, at a first apparatus, a first enrolled feature based on a first feature extractor, obtaining a second enrolled feature to which the first enrolled feature is transformed, determining an input feature by extracting a feature from input data with a second feature extractor different from the first feature extractor, and performing an authentication based on the second enrolled feature and the input feature.

Authentication method and apparatus with transformation model

A processor-implemented method includes generating a preprocessed infrared (IR) image by performing first preprocessing based on an IR image including an object; generating a preprocessed depth image by performing second preprocessing based on a depth image including the object; and determining whether the object is a genuine object based on the preprocessed IR image and the preprocessed depth image.

Method and apparatus with liveness test and/or biometric authentication

A liveness detection method and apparatus, and a facial verification method and apparatus are disclosed. The liveness detection method includes detecting a face region in an input image, measuring characteristic information of the face region, adjusting the measured characteristic information in response to the characteristic information not satisfying a condition, and performing a liveness detection on the face region with the adjusted characteristic information upon the measured characteristic information not satisfying the condition.

Method and apparatus with liveness detection

A face verifying method and apparatus. The face verifying method includes detecting a face region from an input image, generating a synthesized face image by combining image information of the face region and reference image information, based on a determined masking region, extracting one or more face features from the face region and the synthesized face image, performing a verification operation with respect to the one or more face features and predetermined registration information, and indicating whether verification of the input image is successful based on a result of the performed verification operation.

Face verifying method and apparatus

An image matching method includes extracting, from a first image of an object, a landmark patch including a landmark point of the object, extracting, from a second image of the object, a target patch corresponding to the landmark patch; and determining a target point in the second image corresponding to the landmark point based on a matching between the landmark patch and the target patch.

Device and method with image matching

A processor-implemented method includes: generating a preprocessed infrared (IR) image by performing first preprocessing based on an IR image including an object; generating a preprocessed depth image by performing second preprocessing based on a depth image including the object; and determining whether the object is a genuine object based on the preprocessed IR image and the preprocessed depth image.

Liveness test method and apparatus and biometric authentication method and apparatus

The facial verification apparatus is a mobile computing apparatus, including a camera to capture an image, a display, and one or more processors. While in a lock state, the image is captured and facial verification performed using a face image, or using a detected face and in response to the face being detected. The facial verification includes a matching with respect to the detected face, or obtained face image, and a registered face information. If the verification is successful, the lock state of the apparatus may be canceled and the user allowed access to the apparatus. The lock state may be cancelled when the verification is successful and the user has been determined to have been attempting to gain access to the apparatus. Face image feedback to the user may not be displayed during the detecting for, or obtaining of, the face and/or performing of the facial verification.

A three-dimensional (3D) image-based facial verification method and apparatus is provided. The facial verification method may include capturing a facial image of a 3D face of a user, determining an occluded region in the captured facial image by comparing the captured facial image and an average facial image, generating a synthetic image by synthesizing the captured facial image and the average facial image based on the occluded region, and verifying the user based on the synthetic image.

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Suwon-si, South Korea

Minsu Ko