Key strategies for synthetic data generation for training intelligent systems based on people detection from omnidirectional cameras

Nerea Aranjuelo, Sara García, Estíbaliz Loyo, Luis Unzueta, Oihana Otaegui

Abstract: Highlights•Training data are key for the success of Deep Neural Networks and their behaviour.•Synthetic data helps in this process, but the domain gap worsens the results.•Enhancing the generated synthetic data features minimizes the domain gap.•Suitable synthetic samples can improve a model’s generalization ability.