SENSOR DATA ANNOTATION FOR TRAINING MACHINE PERCEPTION MODELS

    公开(公告)号:US20240071060A1

    公开(公告)日:2024-02-29

    申请号:US17893838

    申请日:2022-08-23

    CPC classification number: G06V10/7788 G06V10/46 G06V10/774

    Abstract: Example aspects of the present disclosure relate to an example computer-implemented method for data annotation for training machine perception models. The example method can include (a) receiving source sensor data descriptive of an object, the source sensor data having a source reference frame of at least three dimensions, wherein the source sensor data includes annotated data associated with the object; (b) receiving target sensor data descriptive of the object, the target sensor data having a target reference frame of at least two dimensions; (c) providing an input to a machine-learned boundary recognition model, wherein the input includes the target sensor data and a projection of the source sensor data into the target reference frame; and (d) determining, using the machine-learned boundary recognition model, a bounded portion of the target sensor data, wherein the bounded portion indicates a subset of the target sensor data descriptive of the object.

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