14 citations · 14 across the 6 of their papers we have counts for
4 papers · 1 filter
Expandable Residual Approximation for Knowledge Distillation
Zhaoyi Yan, Binghui Chen, Yunfan Liu +1
Knowledge distillation (KD) aims to transfer knowledge from a large-scale teacher model to a lightweight one, significantly reducing computational and storage requirements. However…
Delving Deep into Semantic Relation Distillation
Zhaoyi Yan, Kangjun Liu, Qixiang Ye
Knowledge distillation has become a cornerstone technique in deep learning, facilitating the transfer of knowledge from complex models to lightweight counterparts. Traditional dist…
Virtual Classification: Modulating Domain-Specific Knowledge for Multidomain Crowd Counting
Mingyue Guo, Binghui Chen, Zhaoyi Yan +2
Multidomain crowd counting aims to learn a general model for multiple diverse datasets. However, deep networks prefer modeling distributions of the dominant domains instead of all…
Regressor-Segmenter Mutual Prompt Learning for Crowd Counting
Mingyue Guo, Li Yuan, Zhaoyi Yan +3
Crowd counting has achieved significant progress by training regressors to predict instance positions. In heavily crowded scenarios, however, regressors are challenged by uncontrol…