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Few-shot keyword spotting with prototypical networks
Few-shot keyword spotting with prototypical networks. -
Few-shot part segmentation for 3D shapes
Few-shot part segmentation for 3D shapes -
Semi Supervised Learning for Few-Shot Audio Classification by Episodic Triple...
Few-shot learning aims to generalize unseen classes that appear during testing but are unavailable during training. The performance of prototypical networks in extreme few-shot... -
Visual Discrimination Puzzles
Visual discrimination puzzles dataset created for few-shot learning problems -
FewCLUE dataset
The FewCLUE dataset is a Chinese few-shot learning evaluation benchmark. -
Colored-Kuzushiji
Colored-Kuzushiji is used for few-shot classification tasks. -
UT-Zappos50K
The UT-Zappos50K dataset is a fine-grained shoe catalog, characterized by its smaller scale and relatively stable and simple content. -
MiniImageNet, TieredImageNet, and CUB
MiniImageNet, TieredImageNet, and CUB are used for few-shot learning tasks. -
Few-shot Name Entity Recognition on StackOverflow
Few-shot Name Entity Recognition on StackOverflow -
miniImageNet, tieredImageNet, Caltech-USCD birds-200-2011
miniImageNet, tieredImageNet, Caltech-USCD birds-200-2011 -
Memory-Augmented Relation Network for Few-Shot Learning
The proposed method Memory-Augmented Relation Network (MRN) for few-shot learning. -
Prototype Refinement Network for Few-Shot Segmentation
Few-shot segmentation targets to segment new classes with few annotated images provided. It is more challenging than traditional semantic segmentation tasks that segment known... -
Eigen-Reptile
The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the Mini-Imagenet and CIFAR-FS datasets for few-shot learning tasks. -
Few-shot Font Generation with Dual Memory
A dataset for few-shot font generation with dual memory. -
PLOT-TAL - Prompt Learning with Optimal Transport for Few-Shot Temporal Actio...
Temporal Action Localization (TAL) in few-shot learning. Our work addresses the inherent limitations of conventional single-prompt learning methods that often lead to... -
Motorbikes
A benchmark dataset for few-shot image-to-image translation -
Carnivores
A benchmark dataset for few-shot image-to-image translation -
COCO-FUNIT
Few-shot unsupervised image-to-image translation with a content conditioned style encoder
