BriefGPT.xyz
Apr, 2023
基于注意力图引导的边缘设备Transformer剪枝
Attention Map Guided Transformer Pruning for Edge Device
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Junzhu Mao, Yazhou Yao, Zeren Sun, Xingguo Huang, Fumin Shen...
TL;DR
研究通过注意力图引导剪枝和键和值矩阵的重要性估计来减少模型大小和推理复杂性,该方法成功地应用在基于ViT的人物再识别模型上,减少了29.4%的FLOPs并提高了0.4%的mAP。
Abstract
Due to its significant capability of modeling long-range dependencies,
vision transformer
(ViT) has achieved promising success in both holistic and occluded
person re-identification
(Re-ID) tasks. However, the in
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