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1.发明申请公开(公告)号：US20200334502A1
公开(公告)日：2020-10-22
申请号：US16921012
申请日：2020-07-06
Applicant: NVIDIA Corporation
Inventor： Wei-Chih Tu , Ming-Yu Liu , Varun Jampani , Deqing Sun , Ming-Hsuan Yang , Jan Kautz
Abstract: Segmentation is the identification of separate objects within an image. An example is identification of a pedestrian passing in front of a car, where the pedestrian is a first object and the car is a second object. Superpixel segmentation is the identification of regions of pixels within an object that have similar properties. An example is identification of pixel regions having a similar color, such as different articles of clothing worn by the pedestrian and different components of the car. A pixel affinity neural network (PAN) model is trained to generate pixel affinity maps for superpixel segmentation. The pixel affinity map defines the similarity of two points in space. In an embodiment, the pixel affinity map indicates a horizontal affinity and vertical affinity for each pixel in the image. The pixel affinity map is processed to identify the superpixels.
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公开(公告)号：US10748036B2
公开(公告)日：2020-08-18
申请号：US16188641
申请日：2018-11-13
Applicant: NVIDIA Corporation
Inventor： Wei-Chih Tu , Ming-Yu Liu , Varun Jampani , Deqing Sun , Ming-Hsuan Yang , Jan Kautz
Abstract: Segmentation is the identification of separate objects within an image. An example is identification of a pedestrian passing in front of a car, where the pedestrian is a first object and the car is a second object. Superpixel segmentation is the identification of regions of pixels within an object that have similar properties An example is identification of pixel regions having a similar color, such as different articles of clothing worn by the pedestrian and different components of the car. A pixel affinity neural network (PAN) model is trained to generate pixel affinity maps for superpixel segmentation. The pixel affinity map defines the similarity of two points in space. In an embodiment, the pixel affinity map indicates a horizontal affinity and vertical affinity for each pixel in the image. The pixel affinity map is processed to identify the superpixels.
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公开(公告)号：US11256961B2
公开(公告)日：2022-02-22
申请号：US16921012
申请日：2020-07-06
Applicant: NVIDIA Corporation
Inventor： Wei-Chih Tu , Ming-Yu Liu , Varun Jampani , Deqing Sun , Ming-Hsuan Yang , Jan Kautz
Abstract: Segmentation is the identification of separate objects within an image. An example is identification of a pedestrian passing in front of a car, where the pedestrian is a first object and the car is a second object. Superpixel segmentation is the identification of regions of pixels within an object that have similar properties. An example is identification of pixel regions having a similar color, such as different articles of clothing worn by the pedestrian and different components of the car. A pixel affinity neural network (PAN) model is trained to generate pixel affinity maps for superpixel segmentation. The pixel affinity map defines the similarity of two points in space. In an embodiment, the pixel affinity map indicates a horizontal affinity and vertical affinity for each pixel in the image. The pixel affinity map is processed to identify the superpixels.
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4.发明申请公开(公告)号：US20190156154A1
公开(公告)日：2019-05-23
申请号：US16188641
申请日：2018-11-13
Applicant: NVIDIA Corporation
Inventor： Wei-Chih Tu , Ming-Yu Liu , Varun Jampani , Deqing Sun , Ming-Hsuan Yang , Jan Kautz
Abstract: Segmentation is the identification of separate objects within an image. An example is identification of a pedestrian passing in front of a car, where the pedestrian is a first object and the car is a second object. Superpixel segmentation is the identification of regions of pixels within an object that have similar properties An example is identification of pixel regions having a similar color, such as different articles of clothing worn by the pedestrian and different components of the car. A pixel affinity neural network (PAN) model is trained to generate pixel affinity maps for superpixel segmentation. The pixel affinity map defines the similarity of two points in space. In an embodiment, the pixel affinity map indicates a horizonal affinity and vertical affinity for each pixel in the image. The pixel affinity map is processed to identify the superpixels.
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