Conditional Patch-Based Domain Randomization: Improving Texture Domain Randomization Using Natural Image Patches
Mohammad Ani,Hector Basevi,Aleš Leonardis,Mohammad Ani,Hector Basevi,Aleš Leonardis
Using Domain Randomized synthetic data for training deep learning systems is a promising approach for addressing the data and the labeling requirements for supervised techniques to bridge the gap between simulation and the real world. We propose a novel approach for generating and applying class-specific Domain Randomization textures by using randomly cropped image patches from real-world data. In...
