Method and apparatus for training a multi-task fusion detection model, multi-task detection method and apparatus

A multi-task detection method, comprising:

• obtaining a trained target multi-task fusion detection model;
• obtaining a target sampling data set to be recognized and inputting the target sampling data set into the target multi-task fusion detection model, and determining, according to the target multi-task fusion detection model, a target detection task to which each target sampling data in the target sampling data set belongs;
• and
• obtaining a detection branch, in the target multi-task fusion detection model, of each target sampling data based on the target detection task, to obtain a target task detection result of each target sampling data;
• wherein the target multi-task fusion detection model is obtained based on a method for training a multi-task fusion detection model, and the method comprises:
• obtaining a single-task detection model of each detection task in a detection task set, and obtaining an initial multi-task fusion detection model to be trained based on each single-task detection model;
• obtaining a training sample set of the initial multi-task fusion detection model by obtaining a single-task sampling data set of each detection task, wherein the training sample set comprises a single-task sample and a multi-task sample;
• and
• training the initial multi-task fusion detection model according to the single-task sample and/or the multi-task sample until the training is completed, to obtain a trained target multi-task fusion detection model.

An electronic device, comprising:

• at least one processor;
• and
• a memory communicatively connected to the at least one processor;
• wherein the memory stores instructions executable by the at least one processor, when the instructions are executed by the at least one processor, the at least one processor is caused to perform a method for training a multi-task fusion detection model, and the method comprises:
• obtaining a single-task detection model of each detection task in a detection task set, and obtaining an initial multi-task fusion detection model to be trained based on each single-task detection model;
• obtaining a training sample set of the initial multi-task fusion detection model by obtaining a single-task sampling data set of each detection task, wherein the training sample set comprises a single-task sample and a multi-task sample;
• and
• training the initial multi-task fusion detection model according to the single-task sample and/or the multi-task sample until the training is completed, to obtain a trained target multi-task fusion detection model.