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公开(公告)号：US20220058779A1
公开(公告)日：2022-02-24
申请号：US17517440
申请日：2021-11-02
Inventor： Zhikang ZOU , Xiaoqing YE , Qu CHEN , Hao SUN
Abstract: The disclosure provides an inpainting method for a human image, an inpainting apparatus for a human image and an electronic device. An image to be processed is received. The image to be processed contains a human image to be processed. A three-dimensional human body model corresponding to the human image to be processed, camera parameters, and human body posture information are generated based on the image to be processed. A segmentation image corresponding to the human image to be processed is generated based on the image to be processed. A processed human image corresponding to the human image to be processed is generated based on the three-dimensional human body model, the camera parameters, the human body posture information, and the segmentation image.
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公开(公告)号：US20210312650A1
公开(公告)日：2021-10-07
申请号：US17353634
申请日：2021-06-21
Inventor： Xiaoqing YE , Hao SUN
Abstract: The present disclosure provides a method of training a depth estimation network, which relates to fields of computer vision, deep learning, and image processing technology. The method includes: performing a depth estimation on an original image by using a depth estimation network, so as to obtain a depth image for the original image; removing a moving object from the original image so as to obtain a preprocessed image for the original image; estimating a pose based on the original image and modifying the pose based on the preprocessed image; and adjusting parameters of the depth estimation network according to the original image, the depth image and the pose modified. The present disclosure further provides an apparatus of training a depth estimation network, a method and apparatus of estimating a depth of an image, an electronic device, and a storage medium.
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Patent Agency Ranking
13.发明公开公开(公告)号：US20230306081A1
公开(公告)日：2023-09-28
申请号：US18054233
申请日：2022-11-10
Inventor： Xiaoqing YE , Ruihang CHU , Hao SUN
CPC classification number: G06K9/6259 , G06K9/6262 , G06K9/6218 , G06K9/6261 , G06T7/11 , G06T2207/10028 , G06T2207/20081
Abstract: A method for training a point cloud processing model and a method for performing instance segmentation on a point cloud are provided. The method includes: labeling an unlabeled point cloud according to a labeled point cloud to obtain a sample point cloud; inputting the sample point cloud to a point cloud processing model to obtain first predicted semantic information of the sample point cloud and a first predicted offset of the sample point cloud; determining a training loss according to the first predicted semantic information, the first predicted offset, a sample label corresponding to the sample point cloud, and original coordinate information of the sample point cloud; and training the point cloud processing model with the training loss.
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公开(公告)号：US20230099113A1
公开(公告)日：2023-03-30
申请号：US17807371
申请日：2022-06-16
Inventor： Xiaoqing YE , Xiao TAN , Hao SUN
Abstract: Provided are a training method and apparatus for a target detection model, a target detection method and apparatus, and a medium. A specific implementation includes inputting a sample image into a point cloud feature extraction network of a first target detection model to obtain an image feature of a generation point cloud; inputting the image feature of the generation point cloud into a first bird's-eye view feature extraction network of the first target detection model to obtain a first bird's-eye view feature; inputting the first bird's-eye view feature into a prediction network of the first target detection model to obtain a first detection result; and calculating a first loss according to a standard 3D recognition result of the sample image and the first detection result and training the first target detection model according to the first loss.
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公开(公告)号：US20230036294A1
公开(公告)日：2023-02-02
申请号：US17936609
申请日：2022-09-29
Inventor： Bo JU , Xiaoqing YE , Xiao TAN , Hao SUN
Abstract: Disclosed are a method for processing an image, an electronic device, and a storage medium. The method includes: acquiring a plurality of point cloud grids from a gridded point cloud map; determining each reference plane with the number of sampling points matched being greater than or equal to a threshold from the initial planes corresponding respectively to the plurality of the point cloud grids; correcting the initial planes corresponding respectively to the plurality of point cloud grids based on each reference plane to obtain target planes corresponding respectively to the plurality of point cloud grids; and performing denoise processing on sampling points based on the target plane of each point cloud grid.
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公开(公告)号：US20220358675A1
公开(公告)日：2022-11-10
申请号：US17869161
申请日：2022-07-20
Inventor： Guanying CHEN , Xiaoqing YE , Xiao TAN , Hao SUN
Abstract: A method and apparatus for training a model, a method and apparatus for processing a video, a device and a storage medium are provided. An implementation of the method for training a model includes: analyzing a sample video, to determine a plurality of human body image frames in the sample video; determining human body-related parameters and camera-related parameters corresponding to each human body image frame; determining, based on the human body-related parameters, the camera-related parameters and an initial model, predicted image parameters of an image plane corresponding to the each human body image frame, the camera-related parameters and image parameters; and training the initial model based on original image parameters of the human body image frames in the sample video and the predicted image parameters of image planes corresponding to the human body image frames, to obtain a target model.
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公开(公告)号：US20210295013A1
公开(公告)日：2021-09-23
申请号：US17340809
申请日：2021-06-07
Inventor： Xiaoqing YE , Xiao TAN , Hao SUN
Abstract: A three-dimensional object detecting method, apparatus, device, and storage medium, where the method includes: detecting an orientation angle and other parameters of a target object; predicting predicted coordinates of vertices of a bottom surface of the target object under two blocking types respectively; accurately determining a corresponding blocking type of the target object by selecting, based on the orientation angle of the target object, predicted coordinates of vertices of the bottom surface matching the orientation angle; using the predicted coordinates of the vertices of the bottom surface of the target object under the corresponding blocking type as coordinates of the vertices of the bottom surface of the target object; and determining a three-dimensional bounding box of the target object according to the predicted coordinates of the vertices of the bottom surface matching the orientation angle and the three-dimensional parameters of the target object.
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