The embodiment of the invention discloses an object attribute identification method and device, a computing device and a system, and the method comprises the steps that the computing device extracts the features of M parts in a first image according to M posture key points to obtain M part feature maps, and then inputs the M part feature maps into a first attribute recognition model to obtain a first attribute recognition result of a target object. Wherein the first image is an original image or an original feature map extracted according to the original image, the original image comprises a target object, the target object comprises M parts, the M attitude key points are in one-to-one correspondence with the M parts, and the M parts are in one-to-one correspondence with the M part featuremaps. According to the embodiment of the invention, before the first attribute recognition model carries out attribute recognition on the target object, the first image is disassembled into M part feature maps irrelevant to the posture of the target object, so that the influence of the posture of the target object on the recognition result is overcome, the attribute recognition of the object is more accurate, and the robustness is good.

本发明实施例公开了一种对象属性的识别方法、装置、计算设备及系统，该方法包括：计算设备根据M个姿态关键点在第一图像中提取M个部位的特征，得到M个部位特征图，进而，将所述M个部位特征图输入第一属性识别模型，得到目标对象的第一属性识别结果。其中，第一图像为原始图像或根据原始图像提取得到的原始特征图，该原始图像包括目标对象，目标对象包括M个部位，M个姿态关键点与M个部位一一对应，M个部位与M个部位特征图一一对应。本发明实施例在第一属性识别模型对目标对象进行属性识别之前，将第一图像拆解出与目标对象姿势无关的M个部位特征图，进而克服目标对象的姿势对识别结果的影响，使得对对象的属性识别更加准确，且鲁棒性好。