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Efficient ViTs

Increasing the efficiency of ViTs without the modification of the architecture. (i.e., Key & Query Sparsification, Token pruning & merging)

Papers

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Showing 1–25 of 32 papers

TitleStatusHype
Token Merging: Your ViT But FasterCode3
Fast Vision Transformers with HiLo AttentionCode2
SPViT: Enabling Faster Vision Transformers via Soft Token PruningCode1
All Tokens Matter: Token Labeling for Training Better Vision TransformersCode1
Castling-ViT: Compressing Self-Attention via Switching Towards Linear-Angular Attention at Vision Transformer InferenceCode1
Chasing Sparsity in Vision Transformers: An End-to-End ExplorationCode1
DiffRate : Differentiable Compression Rate for Efficient Vision TransformersCode1
DynamicViT: Efficient Vision Transformers with Dynamic Token SparsificationCode1
Evo-ViT: Slow-Fast Token Evolution for Dynamic Vision TransformerCode1
GTP-ViT: Efficient Vision Transformers via Graph-based Token PropagationCode1
AdaViT: Adaptive Tokens for Efficient Vision TransformerCode1
Adaptive Token Sampling For Efficient Vision TransformersCode1
Joint Token Pruning and Squeezing Towards More Aggressive Compression of Vision TransformersCode1
Learned Thresholds Token Merging and Pruning for Vision TransformersCode1
Adaptive Sparse ViT: Towards Learnable Adaptive Token Pruning by Fully Exploiting Self-AttentionCode1
Making Vision Transformers Efficient from A Token Sparsification ViewCode1
MDViT: Multi-domain Vision Transformer for Small Medical Image Segmentation DatasetsCode1
Multi-criteria Token Fusion with One-step-ahead Attention for Efficient Vision TransformersCode1
Not All Patches are What You Need: Expediting Vision Transformers via Token ReorganizationsCode1
Global Vision Transformer Pruning with Hessian-Aware SaliencyCode1
Training data-efficient image transformers & distillation through attentionCode1
PPT: Token Pruning and Pooling for Efficient Vision TransformersCode1
Scalable Vision Transformers with Hierarchical PoolingCode1
Pruning Self-attentions into Convolutional Layers in Single PathCode1
ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision TransformerCode1
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