8 citations · 10 across the 12 of their papers we have counts for
8 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…
General Scene Adaptation for Vision-and-Language Navigation
Haodong Hong, Yanyuan Qiao, Sen Wang +2
Vision-and-Language Navigation (VLN) tasks mainly evaluate agents based on one-time execution of individual instructions across multiple environments, aiming to develop agents capa…
TokenBinder: Text-Video Retrieval with One-to-Many Alignment Paradigm
Bingqing Zhang, Zhuo Cao, Heming Du +4
Text-Video Retrieval (TVR) methods typically match query-candidate pairs by aligning text and video features in coarse-grained, fine-grained, or combined (coarse-to-fine) manners.…
Why Only Text: Empowering Vision-and-Language Navigation with Multi-modal Prompts
Haodong Hong, Sen Wang, Zi Huang +2
Current Vision-and-Language Navigation (VLN) tasks mainly employ textual instructions to guide agents. However, being inherently abstract, the same textual instruction can be assoc…
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…