the FaceNet (Schroff et al. 2015) paper. Schroff et al. argued that triplet mining is crucial for model performance and convergence. They also found that the hardest triplets led to local minima early on in training, specifically resulted in collapsed models, whereas semi-hard triplets yields more stable results and faster convergence.