Cycle-object consistency for image-to-image domain adaptation

•In this paper, for the first time, we introduce an instance-aware GAN framework, AugGAN-Det, to jointly train a generator with an object detector (for image-object style) and a discriminator (for global style).•As to the previous instance-aware GAN models, our model internalizes global and object style-transfer without using a detector to extract and explicitly aligning the instance features between the original and the transformed images.•Extensive experimental results demonstrate that our model achieves state-of-the-art performance across different weathers and time-of-day on INIT, GTA, and BDD100k datasets.