FQ-ViT (Swin-S)

Reported on 3 benchmarks across 1 task · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology3 results

QuantizationonImageNet
Activation bits· 2021-11-27
8
FQ-ViT: Post-Training Quantization for Fully Quantized Vision Transformer arXiv:2111.13824
QuantizationonImageNet
Top-1 Accuracy (%)· 2021-11-27
82.71
best: 85.03 (FQ-ViT (ViT-L))
FQ-ViT: Post-Training Quantization for Fully Quantized Vision Transformer arXiv:2111.13824
QuantizationonImageNet
Weight bits· 2021-11-27
8
FQ-ViT: Post-Training Quantization for Fully Quantized Vision Transformer arXiv:2111.13824