In this work, I research methods for style transfer based on Generative Adversarial Network (GAN) and apply them to image retrieval and visual localization. I implement the ToDayGAN model, which can transfer the style of images between different illumination, weather and seasonal conditions. After researching the state-of-the-art visual localization methods on the effect of changing conditions, I apply the style transfer model to implement hierarchical localization, and use SuperPoint to export the dense local descriptors and NetVLAD to export global image-wide descriptors, finally, the SolvePnPRansac pose estimation algorithm is used to obtain a more accurate 6-DoF pose.
The results of ToDayGAN:
The results of applying the style transfer model to implement hierarchical localization.
Aachen的结果：
RobotCar Seasons的结果：
