Abstract: A method is proposed for detecting an object in a 3D scene, further including a detecting model is obtained; the detecting model describes an association relationship between a plurality of base classes of a plurality of objects and 3D data of the plurality of objects. A plurality of open classes of a plurality of candidate objects that are detected in a 3D scene are received, wherein the plurality of open classes comprises the plurality of base classes and at least one novel class not comprised in the plurality of base classes. A 3D portion is detected in 3D data of the 3D scene based on the detecting model and the plurality of open classes, and the 3D portion here corresponds to a target candidate object in the plurality of candidate objects. With the proposed method, objects that belong to a novel class may be detected from the 3D data.

Abstract: A method is proposed for detecting an object in a 3D scene, including obtaining a detecting model that describes an association relationship between a plurality of base classes of a plurality of objects and 3D data of the plurality of objects. A plurality of open classes of a plurality of candidate objects to be detected in a 3D scene are received, the plurality of open classes comprise the plurality of base classes and at least one novel class not in the plurality of base classes. A 3D portion is detected in 3D data of the 3D scene based on the detecting model and the plurality of open classes, the 3D portion corresponds to a target candidate object in the plurality of candidate objects. With this method, objects that belong to a novel class, not annotated in training data of the detecting model, may be detected from the 3D data.

Abstract: A method is proposed for detecting an object in a 3D scene, including obtaining a detecting model that describes an association relationship between a plurality of base classes of a plurality of objects and 3D data of the plurality of objects. A plurality of open classes of a plurality of candidate objects to be detected in a 3D scene are received, the plurality of open classes comprise the plurality of base classes and at least one novel class not in the plurality of base classes. A 3D portion is detected in 3D data of the 3D scene based on the detecting model and the plurality of open classes, the 3D portion corresponds to a target candidate object in the plurality of candidate objects. With this method, objects that belong to a novel class, not annotated in training data of the detecting model, may be detected from the 3D data.