The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Sep. 14, 2021

Filed:

May. 20, 2021
Applicant:

Tsinghua University, Beijing, CN;

Inventors:

Xinyu Zhang, Beijing, CN;

Zhiwei Li, Beijing, CN;

Huaping Liu, Beijing, CN;

Xingang Wu, Beijing, CN;

Assignee:

TSINGHUA UNIVERSITY, Beijing, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/10 (2017.01); G06K 9/00 (2006.01); G06K 9/62 (2006.01);
U.S. Cl.
CPC ...
G06K 9/00791 (2013.01); G06K 9/6289 (2013.01); G06T 7/10 (2017.01); G06T 2207/10024 (2013.01); G06T 2207/10028 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30252 (2013.01);
Abstract

A deep multimodal cross-layer intersecting fusion method, a terminal device and a storage medium are provided. The method includes: acquiring an RGB image and point cloud data containing lane lines, and pre-processing the RGB image and point cloud data; and inputting the pre-processed RGB image and point cloud data into a pre-constructed and trained semantic segmentation model, and outputting an image segmentation result. The semantic segmentation model is configured to implement cross-layer intersecting fusion of the RGB image and point cloud data. In the new method, a feature of a current layer of a current modality is fused with features of all subsequent layers of another modality, such that not only can similar or proximate features be fused, but also dissimilar or non-proximate features can be fused, thereby achieving full and comprehensive fusion of features. All fusion connections are controlled by a learnable parameter.


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