2 citations · 2 across the 4 of their papers we have counts for
5 papers · 1 filter
RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers
Xuwei Xu, Yang Li, Yudong Chen +2
We reveal that feedforward network (FFN) layers, rather than attention layers, are the primary contributors to Vision Transformer (ViT) inference latency, with their impact signify…
No Token Left Behind: Efficient Vision Transformer via Dynamic Token Idling
Xuwei Xu, Changlin Li, Yudong Chen +3
Vision Transformers (ViTs) have demonstrated outstanding performance in computer vision tasks, yet their high computational complexity prevents their deployment in computing resour…
GTP-ViT: Efficient Vision Transformers via Graph-based Token Propagation
Xuwei Xu, Sen Wang, Yudong Chen +3
Vision Transformers (ViTs) have revolutionized the field of computer vision, yet their deployments on resource-constrained devices remain challenging due to high computational dema…
Understanding the Effects of Projectors in Knowledge Distillation
Yudong Chen, Sen Wang, Jiajun Liu +4
Conventionally, during the knowledge distillation process (e.g. feature distillation), an additional projector is often required to perform feature transformation due to the dimens…
Plug n' Play: Channel Shuffle Module for Enhancing Tiny Vision Transformers
Xuwei Xu, Sen Wang, Yudong Chen +1
Vision Transformers (ViTs) have demonstrated remarkable performance in various computer vision tasks. However, the high computational complexity hinders ViTs' applicability on devi…