Influence of Image Quantization on the Sim-to-Real Gap of Synthetically Trained Deep Learning Models
For domains where data is scarce, costly, or privacy-sensitive, synthetic data generation offers a reasonable alternative as a basis for the training of deep learning models. Yet, a persistent challenge arises from the sim-to-real gap, which can deteriorate a synthetically trained model's performance when applied to re...