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Our method consists of two components: Neighbourhood Feature Relationship Distillation and Neighbourhood Logits Relationship Distillation. We perform extensive ...
Our method constructs both spatial similarity informa- tion from intermediate feature maps and similarity distribution information from the final output logits ...
Apr 19, 2024 · A new similarity-based relational knowledge distillation method · 1: SIANet: Support Information-Aware Network for Category-Agnostic Pose ...
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[PDF] Relational Knowledge Distillation - Semantic Scholar
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This paper proposes a new framework and loss function that preserves the semantic similarities of teacher and student training examples.
Knowledge distillation aims at transferring knowledge acquired in one model (a teacher) to another model (a stu- dent) that is typically smaller.
Jul 24, 2024 · Knowledge Distillation (KD) is an advanced technique in machine learning aimed at transferring knowledge from a large, well-trained model, known as the teacher ...
Sep 12, 2024 · We propose a novel method in this paper, called similarity transfer for knowledge distillation (STKD), which aims to fully utilize the similarities between ...
Abstract. Knowledge distillation is a powerful technique for transferring knowledge from a pre-trained teacher model to a student model.
Jul 16, 2024 · By utilizing relational self-supervised dis- tillation to transfer knowledge from a large network to a small network, we enable the training of ...
Most relationship knowledge distillation methods individually optimize pairwise similarities to improve the accuracy performance of a lightweight student ...