The present invention is applied in the technical field of image processing. Disclosed are a multi-task target detection method and apparatus, an electronic device, and a storage medium,. An attention-aware convolutional feature map of a target is extracted using cascaded attention modules, so that attention-aware convolutional features of a whole image can be generated from coarse to fine, to suppress interference of background noise. A local component feature, a global structure feature, a spatial context feature, and a multi-task feature of the target are extracted on the basis of the attention-aware convolutional feature map, and at least one of a detection task, a key point detection task, and an instance segmentation task of the target is implemented on the basis of the local component feature, the global structure feature, the spatial context feature, and the multi-task feature of the target. A global structure, local components, and context information of the target can be effectively associated to form a structured feature expression, thereby enhancing the robustness of the features to shielding, deformation, postures, etc., and improving the multi-task performance.
MULTI-TASK TARGET DETECTION METHOD AND APPARATUS, ELECTRONIC DEVICE, AND STORAGE MEDIUM