Body contour key point detection methods, apparatuses, and devices
AssigneeBeijing Sensetime Technology Development Co., Ltd.
InventorsWentao Liu, Chen Qian, Qinqin Xu
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Abstract
Body contour key point detection methods, image processing methods, neural network training methods, apparatuses, electronic devices, computer-readable storage media, and computer programs include: obtaining an image feature of an image block including a body; obtaining a body contour key point prediction result of the body by means of a first neural network according to the image feature; and obtaining a body contour key point in the image block according to the body contour key point prediction result; where the body contour key point is used for representing an outer contour of the body.
Claims19
A body contour key point detection method, performed by an electronic device, comprising:
- obtaining an image feature of an image block comprising a body;
- obtaining, by means of a first neural network, a body contour key point prediction result of the body according to the image feature;
- and
- obtaining, according to the body contour key point prediction result, a body contour key point in the image block, wherein the body contour key point is used for representing an outer contour of the body,
- wherein the first neural network is trained in advance by means of a training image set comprising body contour key point marking information, wherein the training of the first neural network comprises:
- obtaining an image feature of a sample image block comprising a body;
- obtaining, by means of a first neural network to be trained, a body contour key point prediction result of the body according to the image feature of the sample image block;
- and
- using a difference between the body contour key point prediction result and the body contour key point marking information as guidance information to perform supervised learning on the first neural network to be trained.
An electronic device, comprising:
- a processor;
- and
- a memory for storing instructions executable by the processor;
- wherein execution of the instructions by the processor causes the processor to perform:
- obtaining an image feature of an image block comprising a body;
- obtaining, by means of a first neural network, a body contour key point prediction result of the body according to the image feature;
- and
- obtaining, according to the body contour key point prediction result, a body contour key point in the image block, wherein the body contour key point is used for representing an outer contour of the body,
- wherein the first neural network is trained in advance by means of a training image set comprising body contour key point marking information, wherein the training of the first neural network comprises:
- obtaining an image feature of a sample image block comprising a body;
- obtaining, by means of a first neural network to be trained, a body contour key point prediction result of the body according to the image feature of the sample image block;
- and
- using a difference between the body contour key point prediction result and the body contour key point marking information as guidance information to perform supervised learning on the first neural network to be trained.
A non-transitory computer-readable storage medium, configured to store computer-readable instructions, wherein execution of the instructions by the processor causes the processor to perform:
- obtaining an image feature of an image block comprising a body;
- obtaining, by means of a first neural network, a body contour key point prediction result of the body according to the image feature;
- and
- obtaining, according to the body contour key point prediction result, a body contour key point in the image block, wherein the body contour key point is used for representing an outer contour of the body,
- wherein the first neural network is trained in advance by means of a training image set comprising body contour key point marking information, wherein the training of the first neural network comprises:
- obtaining an image feature of a sample image block comprising a body;
- obtaining, by means of a first neural network to be trained, a body contour key point prediction result of the body according to the image feature of the sample image block;
- and
- using a difference between the body contour key point prediction result and the body contour key point marking information as guidance information to perform supervised learning on the first neural network to be trained.
Dependencies are inferred from the claim text.