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    HUMAN DETECTION IN SCENES
    6.
    发明申请
    HUMAN DETECTION IN SCENES 有权

    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

    IPC: G06K9/00 ,  G06K9/62 ,  G06K9/32 ,  G06N3/08 ,  G06N3/04

    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.

    SELF-IMPROVING DATA ENGINE FOR AUTONOMOUS VEHICLES
    7.
    发明申请
    SELF-IMPROVING DATA ENGINE FOR AUTONOMOUS VEHICLES 有权

    公开(公告)号：US20250148757A1

    公开(公告)日：2025-05-08

    申请号：US18931681

    申请日：2024-10-30

    Applicant: NEC Laboratories America, Inc.

    Inventor： Jong-Chyi Su ,  Sparsh Garg ,  Samuel Schulter ,  Manmohan Chandraker ,  Mingfu Liang

    IPC: G06V10/764 ,  B60W60/00 ,  G06T11/00 ,  G06V10/25 ,  G06V10/44 ,  G06V10/74 ,  G06V20/70

    Abstract: Systems and methods for a self-improving data engine for autonomous vehicles is presented. To train the self-improving data engine for autonomous vehicles (SIDE), multi-modality dense captioning (MMDC) models can detect unrecognized classes from diversified descriptions for input images. A vision-language-model (VLM) can generate textual features from the diversified descriptions and image features from corresponding images to the diversified descriptions. Curated features, including curated textual features and curated image features, can be obtained by comparing similarity scores between the textual features and top-ranked image features based on their likelihood scores. Generate annotations, including bounding boxes and labels, can be generated for the curated features by comparing the similarity scores of labels generated by a zero-shot classifier and the curated textual features. The SIDE can be trained using the curated features, annotations, and feedback.

    Construction zone segmentation
    8.
    发明授权
    Construction zone segmentation 有权

    公开(公告)号：US11580334B2

    公开(公告)日：2023-02-14

    申请号：US17128612

    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 ,  G06K9/62 ,  G06T7/11 ,  G06N3/08 ,  G06V10/25 ,  G06V20/00

    Abstract: Systems and methods for construction zone segmentation 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 construction zones scenes having various objects. 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.

    DOMAIN ADAPTATION FOR INSTANCE DETECTION AND SEGMENTATION
    9.
    发明申请
    DOMAIN ADAPTATION FOR INSTANCE DETECTION AND SEGMENTATION 审中-公开

    公开(公告)号：US20200082221A1

    公开(公告)日：2020-03-12

    申请号：US16535681

    申请日：2019-08-08

    Applicant: NEC Laboratories America, Inc.

    Inventor： Yi-Hsuan Tsai ,  Kihyuk Sohn ,  Buyu Liu ,  Manmohan Chandraker ,  Jong-Chyi Su

    IPC: G06K9/62 ,  G06T7/11

    Abstract: Systems and methods for domain adaptation 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 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.

    AUTOMATIC DATA SYSTEMS FOR NOVEL OBJECT DETECTION
    10.
    发明申请
    AUTOMATIC DATA SYSTEMS FOR NOVEL OBJECT DETECTION 有权

    公开(公告)号：US20250118044A1

    公开(公告)日：2025-04-10

    申请号：US18891590

    申请日：2024-09-20

    Applicant: NEC Laboratories America, Inc.

    Inventor： Jong-Chyi Su ,  Samuel Schulter ,  Sparsh Garg ,  Manmohan Chandraker ,  Mingfu Liang

    IPC: G06V10/25 ,  G06V10/44 ,  G06V10/74 ,  G06V20/70

    Abstract: Systems and methods for identifying novel objects in an image include detecting one or more objects in an image and generating one or more captions for the image. One or more predicted categories of the one or more objects detected in the image and the one or more captions are matched to identify, from the one or more predicted categories, a category of a novel object in the image. An image feature and a text description feature are generated using a description of the novel object. A relevant image is selected using a similarity score between the image feature and the text description feature. A model is updated using the relevant image and associated description of the novel object.

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