47 datasets found

A dataset for few-shot font generation with dual memory.

Temporal Action Localization (TAL) in few-shot learning. Our work addresses the inherent limitations of conventional single-prompt learning methods that often lead to...

A benchmark dataset for few-shot image-to-image translation

Birds dataset consists of 28752 images of birds, each described by a Fisher vector representation.

A benchmark dataset for few-shot image-to-image translation

A benchmark dataset for few-shot image-to-image translation

Few-shot unsupervised image-to-image translation with a content conditioned style encoder

A new approach to meta-learning, called meta-meta classification, to learning in small-data settings.

Few-shot segmentation remains challenging due to the limitations of its labeling information for unseen classes. Most previous approaches rely on extracting high-level feature...

The proposed MG-ViT model is used for few-shot learning on the Agri-ImageNet and ACFR apple detection tasks.

The MiniVSPW dataset is a benchmark for few-shot video object segmentation.

The FewSol dataset is used for training the class-adaptive object detector. It contains 666 objects with a large number of occurrences.

A dataset for training and testing semantically consistent few-shot view synthesis models

The CIFAR-FS dataset is a few-shot learning dataset, consisting of 60,000 color images from 100 classes with 600 examples per class.

The ImageCLEF-DA dataset is a benchmark dataset for ImageCLEF 2014 domain adaptation challenges, which contains 12 categories shared by three domains: Caltech-256 (C), ImageNet...

A dataset of datasets for learning to learn from few examples.

MiniImageNet, Caltech-UCSD Birds 200-2011, TieredImageNet, OfficeHome

Few-shot semantic segmentation via prototype augmentation with image-level annotations

This dataset is used for few-shot novel view synthesis.

The MiniImagenet dataset is a benchmark for few-shot learning, consisting of 60,000 images from 21 classes, each with 300 images.