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公开(公告)号：US20240354336A1
公开(公告)日：2024-10-24
申请号：US18639500
申请日：2024-04-18
Applicant: NEC Laboratories America, Inc.
IPC: G06F16/538 , G06F16/532 , G06F40/30 , G06V10/40 , G06V10/74 , G06V10/94
CPC classification number: G06F16/538 , G06F16/532 , G06F40/30 , G06V10/40 , G06V10/761 , G06V10/945
Abstract: Systems and methods are provided for identifying and retrieving semantically similar images from a database. Semantic analysis is performed on an input query utilizing a vision language model to identify semantic concepts associated with the input query. A preliminary set of images is retrieved from the database for semantic concepts identified. Relevant concepts are extracted for images with a tokenizer by comparing images against a predefined label space to identify relevant concepts. A ranked list of relevant concepts is generated based on occurrence frequency within the set. The preliminary set of images is refined based on selecting specific relevant concepts from the ranked list by the user by combining the input query with the specific relevant concepts. Additional semantic analysis is iteratively performed to retrieve additional sets of images semantically similar to the combined input query and selection of the specific relevant concepts until a threshold condition is met.
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公开(公告)号：US12080100B2
公开(公告)日：2024-09-03
申请号：US17519986
申请日：2021-11-05
Applicant: NEC Laboratories America, Inc.
Inventor： Yumin Suh , Xiang Yu , Yi-Hsuan Tsai , Masoud Faraki , Manmohan Chandraker
IPC: G06V40/16 , G06F18/214 , G06V20/52 , G06V40/10
CPC classification number: G06V40/172 , G06F18/214 , G06V20/52 , G06V40/103
Abstract: A method for employing facial information in unsupervised person re-identification is presented. The method includes extracting, by a body feature extractor, body features from a first data stream, extracting, by a head feature extractor, head features from a second data stream, outputting a body descriptor vector from the body feature extractor, outputting a head descriptor vector from the head feature extractor, and concatenating the body descriptor vector and the head descriptor vector to enable a model to generate a descriptor vector.
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公开(公告)号：US20240233314A1
公开(公告)日：2024-07-11
申请号：US18612606
申请日：2024-03-21
Applicant: NEC Laboratories America, Inc.
Inventor： Yumin Suh , Weijian Deng , Xiang Yu , Masoud Faraki , Manmohan Chandraker , Turgun Kashgari
IPC: G06V10/44 , G06Q30/0601 , G06T7/11 , G06T7/73 , G06V20/52 , G06V40/10 , G06V40/20 , G08B25/00 , G08G1/005 , G08G1/07
CPC classification number: G06V10/454 , G06Q30/0631 , G06T7/11 , G06T7/73 , G06V20/52 , G06V40/103 , G06V40/23 , G08B25/00 , G08G1/005 , G08G1/07
Abstract: A system for rich human analysis includes a memory and one or more processors in communication with the memory configured to extract images from camera in a surveillance system and feed the images to a person detection and tracking system that deciphers human activity tasks. Attributes of persons detected and tracked by the person detection and tracking system are estimated by a rich human analysis system to identify attributes in accordance with set criteria using a set of filters of deeper layers of convolutional layers of a feature extractor where the filters are divided into N groups trained on N corresponding tasks corresponding to task-specific heads such that one task is assigned to each group of the N groups and that each task loss updates only one subset of filters. One or more people that satisfy the attributes and the set criteria are identified.
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公开(公告)号：US20220147761A1
公开(公告)日：2022-05-12
申请号：US17521057
申请日：2021-11-08
Applicant: NEC Laboratories America, Inc.
Inventor： Yi-Hsuan Tsai , Xiang Yu , Bingbing Zhuang , Manmohan Chandraker , Donghyun Kim
Abstract: Video methods and systems include extracting features of a first modality and a second modality from a labeled first training dataset in a first domain and an unlabeled second training dataset in a second domain. A video analysis model is trained using contrastive learning on the extracted features, including optimization of a loss function that includes a cross-domain regularization part and a cross-modality regularization part.
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公开(公告)号：US20220067457A1
公开(公告)日：2022-03-03
申请号：US17412704
申请日：2021-08-26
Applicant: NEC Laboratories America, Inc.
Inventor： Francesco Pittaluga , Giovanni Milione , Xiang Yu , Manmohan Chandraker , Yi-Hsuan Tsai , Zaid Tasneem
Abstract: A method for acquiring privacy-enhancing encodings in an optical domain before image capture is presented. The method includes feeding a differentiable sensing model with a plurality of images to obtain encoded images, the differentiable sensing model including parameters for sensor optics, integrating the differentiable sensing model into an adversarial learning framework where parameters of attack networks, parameters of utility networks, and the parameters of the sensor optics are concurrently updated, and, once adversarial training is complete, validating efficacy of a learned sensor design by fixing the parameters of the sensor optics and training the attack networks and the utility networks to learn to estimate private and public attributes, respectively, from a set of the encoded images.
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Patent Agency Ranking
公开(公告)号：US11055989B2
公开(公告)日：2021-07-06
申请号：US16051924
申请日：2018-08-01
Applicant: NEC Laboratories America, Inc.
Inventor： Kihyuk Sohn , Luan Tran , Xiang Yu , Manmohan Chandraker
IPC: G08G1/017 , G06K9/62 , G06K9/00 , G06N3/08 , G06N3/04 , G06N5/04 , G06T17/00 , G06N20/00 , G08G1/01 , G08G1/04 , G08G1/048 , G06K9/46
Abstract: Systems and methods for performing domain adaptation include collecting a labeled source image having a view of an object. Viewpoints of the object in the source image are synthesized to generate view augmented source images. Photometrics of each of the viewpoints of the object are adjusted to generate lighting and view augmented source images. Features are extracted from each of the lighting and view augmented source images with a first feature extractor and from captured images captured by an image capture device with a second feature extractor. The extracted features are classified using domain adaptation with domain adversarial learning between extracted features of the captured images and extracted features of the lighting and view augmented source images. Labeled target images are displayed corresponding to each of the captured images including labels corresponding to classifications of the extracted features of the captured images.
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公开(公告)号：US10991145B2
公开(公告)日：2021-04-27
申请号：US16673256
申请日：2019-11-04
Applicant: NEC Laboratories America, Inc.
Inventor： Xiang Yu , Feng-Ju Chang , Manmohan Chandraker
Abstract: A system is provided for pose-variant 3D facial attribute generation. A first stage has a hardware processor based 3D regression network for directly generating a space position map for a 3D shape and a camera perspective matrix from a single input image of a face and further having a rendering layer for rendering a partial texture map of the single input image based on the space position map and the camera perspective matrix. A second stage has a hardware processor based two-part stacked Generative Adversarial Network (GAN) including a Texture Completion GAN (TC-GAN) stacked with a 3D Attribute generation GAN (3DA-GAN). The TC-GAN completes the partial texture map to form a complete texture map based on the partial texture map and the space position map. The 3DA-GAN generates a target facial attribute for the single input image based on the complete texture map and the space position map.
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公开(公告)号：US20200151940A1
公开(公告)日：2020-05-14
申请号：US16673256
申请日：2019-11-04
Applicant: NEC Laboratories America, Inc.
Inventor： Xiang Yu , Feng-Ju Chang , Manmohan Chandraker
Abstract: A system is provided for pose-variant 3D facial attribute generation. A first stage has a hardware processor based 3D regression network for directly generating a space position map for a 3D shape and a camera perspective matrix from a single input image of a face and further having a rendering layer for rendering a partial texture map of the single input image based on the space position map and the camera perspective matrix. A second stage has a hardware processor based two-part stacked Generative Adversarial Network (GAN) including a Texture Completion GAN (TC-GAN) stacked with a 3D Attribute generation GAN (3DA-GAN). The TC-GAN completes the partial texture map to form a complete texture map based on the partial texture map and the space position map. The 3DA-GAN generates a target facial attribute for the single input image based on the complete texture map and the space position map.
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公开(公告)号：US10474881B2
公开(公告)日：2019-11-12
申请号：US15888693
申请日：2018-02-05
Applicant: NEC Laboratories America, Inc.
Inventor： Xiang Yu , Kihyuk Sohn , Manmohan Chandraker
Abstract: A video retrieval system is provided that includes a server for retrieving video sequences from a remote database responsive to a text specifying a face recognition result as an identity of a subject of an input image. The face recognition result is determined by a processor of the server, which estimates, using a 3DMM conditioned Generative Adversarial Network, 3DMM coefficients for the subject of the input image. The subject varies from an ideal front pose. The processor produces a synthetic frontal face image of the subject of the input image based on the input image and coefficients. An area spanning the frontal face of the subject is made larger in the synthetic than in the input image. The processor provides a decision of whether the synthetic image subject is an actual person and provides the identity of the subject in the input image based on the synthetic and input images.
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公开(公告)号：US10289822B2
公开(公告)日：2019-05-14
申请号：US15637264
申请日：2017-06-29
Applicant: NEC Laboratories America, Inc. , NEC Hong Kong Limited
Inventor： Manmohan Chandraker , Xiang Yu , Eric Lau , Elsa Wong
IPC: G06K9/00 , G06F21/32 , G06N20/00 , G06N99/00 , G07C9/00 , H04L29/06 , G06F21/62 , G06K9/46 , G06K9/66
Abstract: A face recognition system and corresponding method are provided. The face recognition system includes a camera configured to capture an input image of a subject purported to be a person. The face recognition system further includes a memory storing a deep learning model configured to perform multi-task learning for a pair of tasks including a liveness detection task and a face recognition task. The face recognition system also includes a processor configured to apply the deep learning model to the input image to recognize an identity of the subject in the input image and a liveness of the subject. The liveness detection task is configured to evaluate a plurality of different distractor modalities corresponding to different physical spoofing materials to prevent face spoofing for the face recognition task.
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