Beijing Baidu Netcom Science Technology Co., Ltd

Beijing Baidu Netcom Science and Technology Co., Ltd.

Xiangbo Su

Jian Wang

Hao Sun

Haifeng Wang

Errui Ding

Tian Wu

Jingdong Wang

Zhigang Wang

Tao Hu

Yuchen Yuan

Qiman Wu

Provided are a joint perception model training method, a joint perception method, a device, and a storage medium. The joint perception model training method includes: acquiring sample images and perception tags of the sample images; acquiring a preset joint perception model, where the joint perception model includes a feature extraction network and a joint perception network; performing feature extraction on the sample images through the feature extraction network to obtain target sample features; performing joint perception through the joint perception network according to the target sample features to obtain perception prediction results; and training the preset joint perception model according to the perception prediction results and the perception tags, where the joint perception includes executing at least two perception tasks.

Joint perception model training method, joint perception method, device, and storage medium

A human behavior recognition method, a device, and a storage medium are provided, which are related to the field of artificial intelligence, specifically to computer vision and deep learning technologies, and applicable to smart city scenarios. The method includes: obtaining attribute information of a target object and N pieces of candidate behavior-related information of a target human from a target image, wherein N is an integer greater than or equal to 1; determining target behavior-related information based on comparison results between the N pieces of candidate behavior-related information and the attribute information of the target object; and determining a behavior recognition result of the target human based on the target behavior-related information.

Human behavior recognition method, device, and storage medium

Provided are an image detection method and apparatus, a device, a storage medium and a computer program product, the method includes: performing feature extraction on an image to be detected to obtain a feature map; performing target detection on the feature map through a target branch network to obtain target detection information of candidate anchor boxes at a pixel position of the feature map; performing keypoint detection on the feature map through a keypoint branch network to obtain positions of keypoints in the candidate anchor boxes at the pixel position of the feature map, and generating heatmap groups of the candidate anchor boxes according to the positions of the keypoints; and obtaining information about a target object in the image to be detected and positions of keypoints of the target object according to the target detection information and the heatmap groups.

Image detection method, device, storage medium and computer program product

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Beijing, China

Xiangbo Su