MODELING EQUIVARIANCE IN POINT CLOUDS USING NEURAL NETWORKS FOR THREE-DIMENSIONAL OBJECT DETECTION AND RECOGNITION

    公开(公告)号:US20250131700A1

    公开(公告)日:2025-04-24

    申请号:US18674666

    申请日:2024-05-24

    Abstract: In various examples, a technique for modeling equivariance in point neural networks includes determining a first partition prediction associated with partitioning of a plurality of points included in a scene into a first set of parts. The technique also includes generating, using a neural network, a second partition prediction associated with partitioning of the plurality of points into a second set of parts based at least on one or more aggregations associated with the first set of parts. The technique further includes determining a plurality of piecewise equivariant regions included in the scene based on the second partition prediction and generating an object recognition result associated with the plurality of points based on the plurality of piecewise equivariant regions.

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