-
1.
公开(公告)号:US20240264812A1
公开(公告)日:2024-08-08
申请号:US18613545
申请日:2024-03-22
Inventor: Zhiyu Ding , Zhaosong Huang , Xinxin Huang , Zhiyi Chen , Xiaofeng Deng , Minglei Li , Xiaoyuan Yu , Jing Yuan
IPC: G06F8/38
CPC classification number: G06F8/38
Abstract: An application page development method includes a static page of a target application being first obtained, and then an application page including an interaction function corresponding to interaction description information being generated based on the interaction description information input by a user and the static page. In other words, the application page has a function of interacting with the user.
-
公开(公告)号:US20250056102A1
公开(公告)日:2025-02-13
申请号:US18928653
申请日:2024-10-28
Inventor: Zhiyi Chen , Minglei Li , Yan Cao , Baoxing Huai
IPC: H04N21/81 , G06T13/40 , G06V10/764
Abstract: The application discloses a virtual human video generation method and apparatus. The method includes: obtaining a driving text; obtaining, based on the driving text and an action annotation of a first video, an action type corresponding to the driving text, where the action annotation includes a plurality of action types of a character in the first video; extracting, from the first video based on the action type, an action representation corresponding to the driving text; and generating a virtual human video based on the action representation. According to this application, the virtual human video in which the action of the character is accurate, controllable, and compliant with a preset action specification can be automatically generated, and personalized customization of an action of a virtual human can be implemented by adjusting the action specification.
-
公开(公告)号:US20230206121A1
公开(公告)日:2023-06-29
申请号:US18069822
申请日:2022-12-21
Inventor: Taisong Li , Minglei Li , Yiling Wu , Baoxing Huai , Jing Yuan
IPC: G06N20/00
CPC classification number: G06N20/00
Abstract: A modal information completion method, an apparatus, and a device are provided. A completion apparatus first obtains a modal information group, wherein the modal information group includes at least two pieces of modal information. Then, the completion apparatus may determine, based on an attribute of the modal information group, whether a part or all of first modal information in the modal information group is missing. Subsequently, the completion apparatus determines a target feature vector of the first modal information based on a preset feature vector mapping relationship and a feature vector of second modal information in the modal information group, so that accuracy of the target feature vector of the first modal information is ensured.
-
公开(公告)号:US20240064383A1
公开(公告)日:2024-02-22
申请号:US18496250
申请日:2023-10-27
Inventor: Taisong Li , Minglei Li , Yiling Wu
IPC: H04N21/488 , G06T17/00 , H04N21/845 , G06V40/16 , G10L15/06
CPC classification number: H04N21/4884 , G06T17/00 , H04N21/8456 , G06V40/168 , G10L15/063
Abstract: A method for generating a video corpus is provided, and specifically includes: obtaining a video to be processed, where the video to be processed corresponds to voice content, and some video images of the video to be processed include a subtitle corresponding to the voice content; and obtaining, based on the voice content, a target video clip from the video to be processed, and using a subtitle included in a video image in the target video clip as an annotation text of the target video clip, to obtain a video corpus. In this way, the video corpus can be automatically generated. Impact on segmentation precision caused by a subjective cognitive error in a manual annotation process can be avoided. Further, efficiency of generating the video corpus is generally high.
-
公开(公告)号:US20240020482A1
公开(公告)日:2024-01-18
申请号:US18477082
申请日:2023-09-28
Inventor: Qi Chen , Yi Zheng , Peng Wang , Yu Wang , Minglei Li , Xinyu Duan , Jing Yuan , Baoxing Huai
Abstract: A corpus annotation apparatus obtains a corpus set provided by a user through a client, where the corpus set includes a plurality of semantic categories of corpuses that the user expects to annotate, determines a manual annotation corpus and an automatic annotation corpus falling within a target semantic category in the corpus set, obtains a manual annotation result of the manual annotation corpus, and automatically annotates the automatic annotation corpus based on the manual annotation result of the manual annotation corpus. The manual annotation result and an automatic annotation result that correspond to the automatic annotation corpus are used as training data to train an inference model.
-
-
-
-