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公开(公告)号：US20240153250A1
公开(公告)日：2024-05-09
申请号：US18499649
申请日：2023-11-01
Applicant: NEC Laboratories America, Inc.
Inventor： Bingbing Zhuang , Samuel Schulter , Buyu Liu , Zhixiang Min
IPC: G06V10/774 , G06T7/60 , G06T7/70 , G06V10/82 , G06V20/58
CPC classification number: G06V10/774 , G06T7/60 , G06T7/70 , G06V10/82 , G06V20/58 , G06T2207/20081 , G06T2207/20084 , G06T2207/30261
Abstract: Methods and systems for training a model include training a size estimation model to generate an estimated object size using a training dataset with differing levels of annotation. Two-dimensional object detection is performed on a training image to identify an object. The training image is cropped around the object. A category-level shape reconstruction is generated using a neural radiance field model. A normalized coordinate model is trained using the training image and ground truth information from the category-level shape reconstruction.
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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
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.
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Patent Agency Ranking
33.发明授权公开(公告)号：US11462112B2
公开(公告)日：2022-10-04
申请号：US16787727
申请日：2020-02-11
Applicant: NEC Laboratories America, Inc.
Inventor： Quoc-Huy Tran , Samuel Schulter , Paul Vernaza , Buyu Liu , Pan Ji , Yi-Hsuan Tsai , Manmohan Chandraker
Abstract: A method is provided in an Advanced Driver-Assistance System (ADAS). The method extracts, from an input video stream including a plurality of images using a multi-task Convolutional Neural Network (CNN), shared features across different perception tasks. The perception tasks include object detection and other perception tasks. The method concurrently solves, using the multi-task CNN, the different perception tasks in a single pass by concurrently processing corresponding ones of the shared features by respective different branches of the multi-task CNN to provide a plurality of different perception task outputs. Each respective different branch corresponds to a respective one of the different perception tasks. The method forms a parametric representation of a driving scene as at least one top-view map responsive to the plurality of different perception task outputs. The method controls an operation of the vehicle for collision avoidance responsive to the at least one top-view map indicating an impending collision.
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公开(公告)号：US20220063605A1
公开(公告)日：2022-03-03
申请号：US17408911
申请日：2021-08-23
Applicant: NEC Laboratories America, Inc.
Inventor： Pan Ji , Buyu Liu , Bingbing Zhuang , Manmohan Chandraker , Xiangyu Chen
Abstract: A method provided for 3D object localization predicts pairs of 2D bounding boxes. Each pair corresponds to a detected object in each of the two consecutive input monocular images. The method generates, for each detected object, a relative motion estimation specifying a relative motion between the two images. The method constructs an object cost volume by aggregating temporal features from the two images using the pairs of 2D bounding boxes and the relative motion estimation to predict a range of object depth candidates and a confidence score for each object depth candidate and an object depth from the object depth candidates. The method updates the relative motion estimation based on the object cost volume and the object depth to provide a refined object motion and a refined object depth. The method reconstructs a 3D bounding box for each detected object based on the refined object motion and refined object depth.
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公开(公告)号：US20210150203A1
公开(公告)日：2021-05-20
申请号：US17096111
申请日：2020-11-12
Applicant: NEC Laboratories America, Inc.
Inventor： Buyu Liu , Bingbing Zhuang , Samuel Schulter , Manmohan Chandraker
Abstract: Systems and methods are provided for producing a road layout model. The method includes capturing digital images having a perspective view, converting each of the digital images into top-down images, and conveying a top-down image of time t to a neural network that performs a feature transform to form a feature map of time t. The method also includes transferring the feature map of the top-down image of time t to a feature transform module to warp the feature map to a time t+1, and conveying a top-down image of time t+1 to form a feature map of time t+1. The method also includes combining the warped feature map of time t with the feature map of time t+1 to form a combined feature map, transferring the combined feature map to a long short-term memory (LSTM) module to generate the road layout model, and displaying the road layout model.
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36.发明申请公开(公告)号：US20200286383A1
公开(公告)日：2020-09-10
申请号：US16787727
申请日：2020-02-11
Applicant: NEC Laboratories America, Inc.
Inventor： Quoc-Huy Tran , Samuel Schulter , Paul Vernaza , Buyu Liu , Pan Ji , Yi-Hsuan Tsai , Manmohan Chandraker
Abstract: A method is provided in an Advanced Driver-Assistance System (ADAS). The method extracts, from an input video stream including a plurality of images using a multi-task Convolutional Neural Network (CNN), shared features across different perception tasks. The perception tasks include object detection and other perception tasks. The method concurrently solves, using the multi-task CNN, the different perception tasks in a single pass by concurrently processing corresponding ones of the shared features by respective different branches of the multi-task CNN to provide a plurality of different perception task outputs. Each respective different branch corresponds to a respective one of the different perception tasks. The method forms a parametric representation of a driving scene as at least one top-view map responsive to the plurality of different perception task outputs. The method controls an operation of the vehicle for collision avoidance responsive to the at least one top-view map indicating an impending collision.
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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
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.
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