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cs.SD2025
Metric Learning with Progressive Self-Distillation for Audio-Visual Embedding Learning
Donghuo Zeng, Kazushi Ikeda
Metric learning projects samples into an embedded space, where similarities and dissimilarities are quantified based on their learned representations. However, existing methods oft…
cs.SD2024★ 1 cited
Anchor-aware Deep Metric Learning for Audio-visual Retrieval
Donghuo Zeng, Yanan Wang, Kazushi Ikeda +1
Metric learning minimizes the gap between similar (positive) pairs of data points and increases the separation of dissimilar (negative) pairs, aiming at capturing the underlying da…
cs.SD2023★ 1 cited
Two-Stage Triplet Loss Training with Curriculum Augmentation for Audio-Visual Retrieval
Donghuo Zeng, Kazushi Ikeda
The cross-modal retrieval model leverages the potential of triple loss optimization to learn robust embedding spaces. However, existing methods often train these models in a singul…