Right: Learned Semantic transformation of the object in the Left Image


Todays world is hugely driven by data. Data, however, in certain scenarios is extremely scarce. A common solution in these scenarios is data augmentation. Data augmentation in general, means transforming data to increase the total amount of data available. Classic data augmentation approaches for images include, cropping, resizing, rotating, illumination changes etc. In this line of research we are focusing on learning Image augmentation techniques. This allows for semantically meaningful changes to an image. For example, we could change the color of an object of interest like the car that is shown above.


Due to recent advances in the development of Deep Generative Models, we are nowadays able to do semantic data augmentation and produce new photorealistic examples.


For more information please contact  Stephan Brehm.