30 citations · 106 across the 17 of their papers we have counts for
Showing 2021Show all
3 papers · 1 filter
cs.CV2021★ 2 cited
Self-supervised Feature-Gate Coupling for Dynamic Network Pruning
Mengnan Shi, Chang Liu, Jianbin Jiao +1
Gating modules have been widely explored in dynamic network pruning to reduce the run-time computational cost of deep neural networks while preserving the representation of feature…
cs.CV2021★ 4 cited
Learnable Expansion-and-Compression Network for Few-shot Class-Incremental Learning
Boyu Yang, Mingbao Lin, Binghao Liu +4
Few-shot class-incremental learning (FSCIL), which targets at continuously expanding model's representation capacity under few supervisions, is an important yet challenging problem…
cs.CV2021★ 9 cited
Beyond Max-Margin: Class Margin Equilibrium for Few-shot Object Detection
Bohao Li, Boyu Yang, Chang Liu +3
Few-shot object detection has made substantial progressby representing novel class objects using the feature representation learned upon a set of base class objects. However,an imp…