Tip-Adapter: 基于CLIP进行few-shot分类的免训练自适应方法。具体做法:以非参数的方式从few-shot训练集构建key-value缓存模型。 背景介绍 CLIP[1]提出从成对的自然语言监督中学习可迁移的视觉特征,进而无需重新训练,并展现出强大的零样本图像分类能力。 CoOp[2]在CLIP的基础上通过构建可学习的文本token对预训练的CL...
基于Tip-Adapter 的网络结构,我们可以进一步将 Cache Model 中的 Keys 部分变为学习参数,即可以通过训练来进行更新,该方案为 Tip-Adapter-F。借助已经构建好的 Cache Model,Tip-Adapter-F 仅需要现有 CLIP-Adapter 十分之一的训练回合数和时间,就可以实现更高的性能,如表一所示。 图1:Tip-Adapter 和 Tip-Adapt...
提出Training - free CLIP - Adapter(Tip - Adapter):采用CLIP - Adapter的架构设计,通过从少样本监督中构建查询 - 键缓存模型来获取适配器的权重,避免了传统的SGD微调,在少样本分类任务中具有较强性能。 性能可通过微调进一步提高:基于构建的权重进行微调,能够以超快的收敛速度显著提升Tip - Adapter的性能。 在多...
Tip-Adapter constructs the adapter via a key-value cache model from the few-shot training set, and updates the prior knowledge encoded in CLIP by feature retrieval. On top of that, the performance of Tip-Adapter can be further boosted to be state-of-the-art on ImageNet by fine-tuning ...
Tip-Adapter does not require any back propagation for training the adapter, but creates the weights by a key-value cache model constructed from the few-shot training set. In this non-parametric manner, Tip-Adapter acquires well-performed adapter weights without any training, which is both ...
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TIP ADAPTER - METRIC - M3/M2 E 210156 可售卖地 全国 示例型号:TIP ADAPTER - METRIC - M3/M2 EXT/INT 210156 价格说明 价格:商品在爱采购的展示标价,具体的成交价格可能因商品参加活动等情况发生变化,也可能随着购买数量不同或所选规格不同而发生变化,如用户与商家线下达成协议,以线下协议的结算价格为准...
git clone https://github.com/gaopengcuhk/Tip-Adapter.gitcdTip-Adapter conda create -n tip_adapter python=3.7 conda activate tip_adapter pip install -r requirements.txt#Install the according versions of torch and torchvisionconda install pytorch torchvision cudatoolkit ...
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Tip-Adapter constructs the adapter via a key-value cache model from the few-shot training set, and updates the prior knowledge encoded in CLIP by feature retrieval. On top of that, the performance of Tip-Adapter can be further boosted to be state-of-the-art on ImageNet by fine-tuning ...