论文:Han-Jia Ye, Hexiang Hu, De-Chuan Zhan, Fei Sha. Few-Shot Learning via Embedding Adaptation with Set-to-Set Functions. CVPR, 2020 在深度学习时代,基于少量数据学习视觉模型具有非常强大的挑战性。目前大部分小样本学习方法都是基于已知类数据学习视觉模型,然后迁移到新的小样本数据中。这类方法学习的...
由下式得到最终embedding,由于同类样本间可以传递信息,所以也是一种考虑全局的embedding方式。 计算公式和解释 Transformer:正常的scaled dot-product attention。 既然已经得到了我们的set2set embedding,接下来可以借助self-supervision 中的contrastive learning来增强我们模型,主要引入对应contrastive learning loss。 c_n为p...
在FSL,因为一个episode中support set是有标签的,所以cross entropy可以作为第一个损失项用来约束encoder输出的support embedding与label之间的关系。第二个loss是在predicted feature embedding和real feature embeddings之间的MSE损失,注意这第二个loss不是逐像素的,而是度量的embedding之间的MSE。第三个loss是为了确保重构出...
Adaptive subspaces for few-shot learning; Interventional few-shot learning; Dpgn: Distribution propagation graph network for few-shot learning; When does self-supervision improve few-shot learning?; Few-shot learning via embedding adaptation with set-to-set functions; Laplacian regularized few-...
We denote this model as FEAT (few-shot\nembedding adaptation w/ Transformer) and validate it on both the standard\nfew-shot classification benchmark and four extended few-shot learning settings\nwith essential use cases, i.e., cross-domain, transductive, generalized\nfew-shot learning, and ...
Code AddRemoveMark official Sha-Lab/FEATofficial 418 sicara/easy-few-shot-learning ↳ Quickstart in Colab 1,065 Alibaba-AAIG/SSL-FEW-SHOT 171 danielshalam/bpa 51 DanielShalam/SOT 51 See all 6implementations Tasks Edit AddRemove Datasets
Ye HJ, Hu H, Zhan DC, et al (2020) Few-shot learning via embedding adaptation with set-to-set functions. In: Proc. of CVPR, pp 8808–8817 Young S, Gašić M, Thomson B, et al (2013) Pomdp-based statistical spoken dialog systems: A review. In: IEEE, pp 1160–1179 Yu D, ...
Few- shot learning via embedding adaptation with set-to-set func- tions. In CVPR, pages 8808–8817, 2020. 14419 [31] Chi Zhang, Yujun Cai, Guosheng Lin, and Chunhua Shen. Deepemd: Differentiable earth mover's distance for few-shot learning. arXiv e-...
ESFR: Unsupervised Embedding Adaptation via Early-Stage Feature Reconstruction for Few-Shot Classification 论文链接: arxiv.org/abs/2106.1148 开源代码: github.com/moving…阅读全文 赞同41 1 条评论 分享收藏 举一隅而以三隅反,MMFewShot 带你走近少样本学习【MMFewshot重磅开源!】 ...
Learning to learn dense gaussian processes for few-shot learning. Advances in Neural Information Processing Sys- tems, 34, 2021. [40] Han-Jia Ye, Hexiang Hu, De-Chuan Zhan, and Fei Sha. Few- shot learning via embedding adaptation with set-to-set func- tions. In IEEE/CVF ...