Few-Shot Object Detection as a Service: Facilitating Training and Deployment for Domain Experts
摘要
We propose a service-based approach for training few-shot object detectors and running inference with these models. This eliminates the need to write code or execute scripts, thus enabling domain experts to train their own detectors. The training service implements an efficient ensemble learning method in order to obtain more robust models without parameter search. The entire pipeline is deployed as a single container and can be controlled from a web user interface.