A common architectural choice for deep metric learning is a convolutional neural network
followed by global average pooling (GAP). Albeit simple, GAP is a highly effective way to …

Typical technique in knowledge distillation (KD) is regularizing the learning of a limited
capacity model (student) by pushing its responses to match a powerful model's (teacher) …

Known as the key to the success of many neural networks (CNNs), convolutional blocks
serve as local feature extractors. Yet, explicit supervision of intermediate layers becomes a …