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公开(公告)号：US11594041B2
公开(公告)日：2023-02-28
申请号：US17128492
申请日：2020-12-21
Applicant: NEC Laboratories America, Inc.
Inventor： Yi-Hsuan Tsai , Kihyuk Sohn , Buyu Liu , Manmohan Chandraker , Jong-Chyi Su
IPC: G06K9/00 , G06V20/58 , G06K9/62 , B60W30/095 , B60W30/09 , B60W10/18 , B60W10/20 , G08G1/16 , B60W50/00 , G06N3/08 , G06N3/04
Abstract: Systems and methods for obstacle detection are provided. The system aligns image level features between a source domain and a target domain based on an adversarial learning process while training a domain discriminator. The target domain includes one or more road scenes having obstacles. The system selects, using the domain discriminator, unlabeled samples from the target domain that are far away from existing annotated samples from the target domain. The system selects, based on a prediction score of each of the unlabeled samples, samples with lower prediction scores. The system annotates the samples with the lower prediction scores.
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公开(公告)号：US20220108226A1
公开(公告)日：2022-04-07
申请号：US17491663
申请日：2021-10-01
Applicant: NEC Laboratories America, Inc.
Inventor： Xiang Yu , Yi-Hsuan Tsai , Francesco Pittaluga , Masoud Faraki , Manmohan Chandraker , Yuqing Zhu
Abstract: A method for employing a general label space voting-based differentially private federated learning (DPFL) framework is presented. The method includes labeling a first subset of unlabeled data from a first global server, to generate first pseudo-labeled data, by employing a first voting-based DPFL computation where each agent trains a local agent model by using private local data associated with the agent, labeling a second subset of unlabeled data from a second global server, to generate second pseudo-labeled data, by employing a second voting-based DPFL computation where each agent maintains a data-independent feature extractor, and training a global model by using the first and second pseudo-labeled data to provide provable differential privacy (DP) guarantees for both instance-level and agent-level privacy regimes.
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13.发明授权公开(公告)号：US11250282B2
公开(公告)日：2022-02-15
申请号：US17091140
申请日：2020-11-06
Applicant: NEC Laboratories America, Inc.
Inventor： Xiang Yu , Buyu Liu , Manmohan Chandraker , Junru Wu
Abstract: A computer-implemented method for implementing face spoofing detection using a physical-cue-guided multi-source multi-channel framework includes receiving a set of data including face recognition data, liveness data and material data associated with at least one face image, obtaining a shared feature from the set of data using a backbone neural network structure, performing, based on the shared feature, a pretext task corresponding to face recognition, a first proxy task corresponding to depth estimation, a liveness detection task, and a second proxy task corresponding to material prediction, and aggregating outputs of the pretext task, the first proxy task, the liveness detection task and the second proxy task using an attention mechanism to boost face spoofing detection performance.
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公开(公告)号：US11222210B2
公开(公告)日：2022-01-11
申请号：US16673156
申请日：2019-11-04
Applicant: NEC Laboratories America, Inc.
Inventor： Gaurav Sharma , Manmohan Chandraker
Abstract: A computer-implemented method is provided for domain adaptation between a source domain and a target domain. The method includes applying, by a hardware processor, an attention network to features extracted from images included in the source and target domains to provide attended features relating to a given task to be domain adapted between the source and target domains. The method further includes applying, by the hardware processor, a deformation network to at least some of the attended features to align the attended features between the source and target domains using warping to provide attended and warped features. The method also includes training, by the hardware processor, a target domain classifier using the images from the source domain. The method additionally includes classifying, by the hardware processor using the trained target domain classifier, at least one image from the target domain.
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公开(公告)号：US20210158490A1
公开(公告)日：2021-05-27
申请号：US17090508
申请日：2020-11-05
Applicant: NEC Laboratories America, Inc.
Inventor： Quoc-Huy Tran , Bingbing Zhuang , Pan Ji , Manmohan Chandraker
Abstract: A method for jointly removing rolling shutter (RS) distortions and blur artifacts in a single input RS and blurred image is presented. The method includes generating a plurality of RS blurred images from a camera, synthesizing RS blurred images from a set of GS sharp images, corresponding GS sharp depth maps, and synthesized RS camera motions by employing a structure-and-motion-aware RS distortion and blur rendering module to generate training data to train a single-view joint RS correction and deblurring convolutional neural network (CNN), and predicting an RS rectified and deblurred image from the single input RS and blurred image by employing the single-view joint RS correction and deblurring CNN.
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Patent Agency Ranking
公开(公告)号：US20210150751A1
公开(公告)日：2021-05-20
申请号：US17095967
申请日：2020-11-12
Applicant: NEC Laboratories America, Inc.
Inventor： Buyu Liu , Samuel Schulter , Manmohan Chandraker
Abstract: Methods and systems for occlusion detection include detecting a set of foreground object masks in an image, including a mask of a visible portion of a foreground object and a mask of the foreground object that includes at least one occluded portion, using a machine learning model. A set of background object masks is detected in the image, including a mask of a visible portion of a background object and a mask of the background object that includes at least one occluded portion, using the machine learning model. The set of foreground object masks and the set of background object masks are merged using semantic merging. A computer vision task is performed that accounts for the at least one occluded portion of at least one object of the merged set.
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公开(公告)号：US20210150275A1
公开(公告)日：2021-05-20
申请号：US17094261
申请日：2020-11-10
Applicant: NEC Laboratories America, Inc.
Inventor： Samuel Schulter , Gaurav Sharma , Yi-Hsuan Tsai , Manmohan Chandraker , Xiangyun Zhao
Abstract: Methods and systems for object detection include training dataset-specific object detectors using respective annotated datasets, each of the annotated datasets including annotations for a respective set of one or more object classes. The annotated datasets are cross-annotated using the dataset-specific object detectors. A unified object detector is trained, using the cross-annotated datasets, to detect all of the object classes of the annotated datasets. Objects are detected in an input image using the unified object detector.
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18.发明申请公开(公告)号：US20210150240A1
公开(公告)日：2021-05-20
申请号：US17091140
申请日：2020-11-06
Applicant: NEC Laboratories America, Inc.
Inventor： Xiang Yu , Buyu Liu , Manmohan Chandraker , Junru Wu
Abstract: A computer-implemented method for implementing face spoofing detection using a physical-cue-guided multi-source multi-channel framework includes receiving a set of data including face recognition data, liveness data and material data associated with at least one face image, obtaining a shared feature from the set of data using a backbone neural network structure, performing, based on the shared feature, a pretext task corresponding to face recognition, a first proxy task corresponding to depth estimation, a liveness detection task, and a second proxy task corresponding to material prediction, and aggregating outputs of the pretext task, the first proxy task, the liveness detection task and the second proxy task using an attention mechanism to boost face spoofing detection performance.
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公开(公告)号：US20210148727A1
公开(公告)日：2021-05-20
申请号：US17090399
申请日：2020-11-05
Applicant: NEC Laboratories America, Inc.
Inventor： Sriram Nochur Narayanan , Manmohan Chandraker
Abstract: A method for simultaneous multi-agent recurrent trajectory prediction is presented. The method includes reconstructing a topological layout of a scene from a dataset including real-world data, generating a road graph of the scene, the road graph capturing a hierarchical structure of interconnected lanes, incorporating vehicles from the scene on the generated road graph by utilizing tracklet information available in the dataset, assigning the vehicles to their closest lane identifications, and identifying diverse plausible behaviors for every vehicle in the scene. The method further includes sampling one behavior from the diverse plausible behaviors to select an associated velocity profile sampled from the real-world data of the dataset that resembles the sampled one behavior and feeding the road graph and the sampled velocity profile with a desired destination to a dynamics simulator to generate a plurality of simulated diverse trajectories output on a visualization device.
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公开(公告)号：US20210110147A1
公开(公告)日：2021-04-15
申请号：US17128565
申请日：2020-12-21
Applicant: NEC Laboratories America, Inc.
Inventor： Yi-Hsuan Tsai , Kihyuk Sohn , Buyu Liu , Manmohan Chandraker , Jong-Chyi Su
Abstract: Systems and methods for human detection are provided. The system aligns image level features between a source domain and a target domain based on an adversarial learning process while training a domain discriminator. The target domain includes humans in one or more different scenes. The system selects, using the domain discriminator, unlabeled samples from the target domain that are far away from existing annotated samples from the target domain. The system selects, based on a prediction score of each of the unlabeled samples, samples with lower prediction scores. The system annotates the samples with the lower prediction scores.
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