Patent ID: 11868438
Assignee: BEIJING QINGZHOUZHIHANG INTELLIGENT TECHNOLOGY CO., LTD
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A method for self-supervised learning, comprising:
acquiring an unlabeled dataset, wherein the dataset comprises point clouds in a plurality of frames, and a point cloud in each of the plurality of frames comprises a plurality of real points;
organizing real points in one column along a vertical direction into a pillar, wherein the pillar is provided with a pillar motion parameter, and each of the real points in the pillar has a motion parameter that is the same as the pillar motion parameter;
for each of real points in a current frame, moving the real point to a next frame based on a corresponding pillar motion parameter, and determining a predicted point in the next frame;
determining a first loss term based on a minimum distance among distances between predicted points in the next frame and real points in the next frame, and generating a loss function comprising the first loss term; and
performing self-supervised learning processing based on the loss function to determine a pillar motion parameter of the pillar.