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:
Apr. 21, 2026

Filed:

Nov. 04, 2024
Applicant:

Shanghai Artificial Intelligence Innovation Center, Shanghai, CN;

Inventors:

Hongyang Li, Shanghai, CN;

Li Chen, Shanghai, CN;

Shenyuan Gao, Shanghai, CN;

Jiazhi Yang, Shanghai, CN;

Yihang Qiu, Shanghai, CN;

Chonghao Sima, Shanghai, CN;

Tianyu Li, Shanghai, CN;

Jia Zeng, Shanghai, CN;

Yang Li, Shanghai, CN;

Huijie Wang, Shanghai, CN;

Junchi Yan, Shanghai, CN;

Ping Luo, Shanghai, CN;

Yu Qiao, Shanghai, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 20/56 (2022.01); G06T 5/70 (2024.01); G06T 7/20 (2017.01);
U.S. Cl.
CPC ...
G06V 20/56 (2022.01); G06T 5/70 (2024.01); G06T 7/20 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30241 (2013.01); G06T 2207/30252 (2013.01);
Abstract

Provided method for training an autonomous driving model including a video prediction model, and the method including: determining, according to at least one of an initial video frame collected by a target vehicle or scenario description metadata of an initial video frame, a scenario context of the initial video frame; determining a vehicle movement instruction of the target vehicle according to at least one of the initial video frame or trajectory data of the target vehicle corresponding to the initial video frame; and training an initial model using the initial video frame and a control text corresponding to the initial video frame, to obtain the video prediction model, where the control text comprises the scenario context and the vehicle movement instruction, and the video prediction model is configured to output a predicted video frame.


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