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Few-Shot Image Classification datasets

archive 2025-07-28

24 datasets carry the task tag "Few-Shot Image Classification" (the task itself: Few-Shot Image Classification), ordered by the archive's paper count. Page 1 of 1: 24 shown of 24. Facet routes are this site's own (the archive records the tag string, not a page).

The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.

Filter 51 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets

All 12,172 Question Answering 413Semantic Segmentation 347Object Detection 332Image Classification 283Classification 222Text Classification 167Language Modelling 166Text Generation 162Visual Question Answering (VQA) 144Named Entity Recognition (NER) 130Pose Estimation 124Anomaly Detection 119Action Recognition 115Instance Segmentation 111Sentiment Analysis 104Text Summarization 98Domain Adaptation 96Speech Recognition 96Reading Comprehension 95Information Retrieval 932D Object Detection 92Image Retrieval 87Machine Translation 82Relation Extraction 822D Semantic Segmentation 81Natural Language Inference 81Image Captioning 79Image Generation 79Depth Estimation 77Node Classification 75Natural Language Understanding 72Autonomous Driving 70Code Generation 70Object Tracking 693D Object Detection 67Face Recognition 67Link Prediction 67Person Re-Identification 65Data Augmentation 63Multi-Task Learning 593D Reconstruction 58Common Sense Reasoning 56Recommendation Systems 56Video Understanding 56Optical Character Recognition (OCR) 55Graph Classification 54Abstractive Text Summarization 52Emotion Recognition 52Medical Image Segmentation 52Word Embeddings 52Few-Shot Image Classification 24

Few-Shot Image Classification datasets 1–24 of 24

ImageNet
The ImageNet dataset contains 14,197,122 annotated images according to the WordNet hierarchy.
ImagesImage ClassificationClassificationImage GenerationZero-Shot LearningVisual Question Answering (VQA)Few-Shot Image Classification+37 tasks
15,430 papers · 52 benchmarks
CIFAR-100
The CIFAR-100 dataset (Canadian Institute for Advanced Research, 100 classes) is a subset of the Tiny Images dataset and consists of 60000 32x32 color images.
ImagesImage ClassificationClassificationImage GenerationZero-Shot LearningAnomaly DetectionFew-Shot Image Classification+37 tasks
9,045 papers · 51 benchmarks
CUB-200-2011 (Caltech-UCSD Birds-200-2011)
The Caltech-UCSD Birds-200-2011 (CUB-200-2011) dataset is the most widely-used dataset for fine-grained visual categorization task.
ImagesImage ClassificationImage GenerationZero-Shot LearningFew-Shot Image ClassificationImage RetrievalFew-Shot Learning+29 tasks
2,235 papers · 47 benchmarks
mini-Imagenet
mini-Imagenet is proposed by Matching Networks for One Shot Learning .
Few-Shot Image ClassificationFew-Shot LearningContinual LearningCross-Domain Few-ShotUnsupervised Few-Shot Image ClassificationFew-Shot Class-Incremental Learning
1,345 papers · 21 benchmarks
Oxford 102 Flower (102 Category Flower Dataset)
Oxford 102 Flower is an image classification dataset consisting of 102 flower categories.
ImagesImage ClassificationImage GenerationZero-Shot LearningFew-Shot Image ClassificationFew-Shot LearningContinual Learning+10 tasks
1,307 papers · 16 benchmarks
Stanford Cars
The Stanford Cars dataset consists of 196 classes of cars with a total of 16,185 images, taken from the rear.
ImagesImage ClassificationImage GenerationZero-Shot LearningFew-Shot Image ClassificationFew-Shot LearningContinual Learning+7 tasks
790 papers · 13 benchmarks
iNaturalist
The iNaturalist 2017 dataset (iNat) contains 675,170 training and validation images from 5,089 natural fine-grained categories.
ImagesImage ClassificationImage GenerationFew-Shot Image ClassificationImage RetrievalFine-Grained Image ClassificationLong-tail Learning+1 tasks
603 papers · 12 benchmarks
Caltech-256
Caltech-256 is an object recognition dataset containing 30,607 real-world images, of different sizes, spanning 257 classes (256 object classes and an additional clutter class).
ImagesImage ClassificationFew-Shot Image ClassificationSemi-Supervised Image Classification
401 papers · 4 benchmarks
tieredImageNet
The tieredImageNet dataset is a larger subset of ILSVRC-12 with 608 classes (779,165 images) grouped into 34 higher-level nodes in the ImageNet human-curated hierarchy.
ImagesImage ClassificationFew-Shot Image ClassificationUnsupervised Few-Shot Image Classification
317 papers · 7 benchmarks
AwA (Animals with Attributes)
Animals with Attributes (AwA) was a dataset for benchmarking transfer-learning algorithms, in particular attribute base classification.
ImagesZero-Shot LearningFew-Shot Image ClassificationGeneralized Few-Shot LearningGeneralized Zero-Shot LearningConcept-based ClassificationLong-tail learning with class descriptors
264 papers · 3 benchmarks
AwA2 (Animals with Attributes 2)
Animals with Attributes 2 (AwA2) is a dataset for benchmarking transfer-learning algorithms, such as attribute base classification and zero-shot learning.
ImagesZero-Shot LearningFew-Shot Image ClassificationGeneralized Few-Shot LearningGeneralized Zero-Shot LearningConcept-based Classification
231 papers · 5 benchmarks
CIFAR-FS (CIFAR100 few-shots)
CIFAR100 few-shots (CIFAR-FS) is randomly sampled from CIFAR-100 (Krizhevsky & Hinton, 2009) by using the same criteria with which miniImageNet has been generated.
ImagesFew-Shot Image Classification
206 papers · 2 benchmarks
aPY (Attribute Pascal and Yahoo)
aPY is a coarse-grained dataset composed of 15339 images from 3 broad categories (animals, objects and vehicles), further divided into a total of 32 subcategories (aeroplane, …, zebra).
ImagesZero-Shot LearningFew-Shot Image ClassificationGeneralized Zero-Shot LearningConcept-based Classification
147 papers · 5 benchmarks
FC100 (Fewshot-CIFAR100)
The FC100 dataset (Fewshot-CIFAR100) is a newly split dataset based on CIFAR-100 for few-shot learning.
ImagesFew-Shot Image Classification
137 papers · 5 benchmarks
Meta-Dataset
The Meta-Dataset benchmark is a large few-shot learning benchmark and consists of multiple datasets of different data distributions.
ImagesImage ClassificationFew-Shot Image ClassificationMeta-LearningFew-Shot Learning
128 papers · 2 benchmarks
Stanford Dogs
The Stanford Dogs dataset contains 20,580 images of 120 classes of dogs from around the world, which are divided into 12,000 images for training and 8,580 images for testing.
ImagesImage GenerationFew-Shot Image ClassificationImage ClusteringFine-Grained Image ClassificationFine-Grained Visual Recognition
57 papers · 6 benchmarks
UT Zappos50K
UT Zappos50K is a large shoe dataset consisting of 50,025 catalog images collected from Zappos.com.
Image GenerationFew-Shot Image ClassificationImage-to-Image TranslationImage CaptioningCompositional Zero-Shot Learning
32 papers · 2 benchmarks
SUN (SUN Database)
When glancing at a magazine, or browsing the Internet, we are continuously being exposed to photographs.
ImagesFew-Shot Image ClassificationGeneralized Few-Shot LearningZero-Shot Transfer Image ClassificationLong-tail learning with class descriptors
31 papers · 4 benchmarks
Bongard-HOI
Bongard-HOI testifies to which extent your few-shot visual learner can quickly induce the true HOI concept from a handful of images and perform reasoning with it.
ImagesTextsFew-Shot Image Classification
12 papers · 1 benchmark
ArtBench-10 (32x32)
We introduce ArtBench-10, the first class-balanced, high-quality, cleanly annotated, and standardized dataset for benchmarking artwork generation.
ImagesImage ClassificationImage GenerationFew-Shot Image ClassificationConditional Image GenerationUnconditional Image Generation
7 papers · 1 benchmark
ORBIT
ORBIT is a real-world few-shot dataset and benchmark grounded in a real-world application of teachable object recognizers for people who are blind/low vision.
ImagesVideosFew-Shot Image ClassificationFew-Shot Learning
7 papers · 2 benchmarks
FewSOL (A Dataset for Few-Shot Object Learning in Robotic Environments)
The Few-Shot Object Learning (FewSOL) dataset can be used for object recognition with a few images per object.
ImagesTextsRGB-D6DPose EstimationFew-Shot Image ClassificationFew-Shot LearningFew-Shot Semantic SegmentationObject RecognitionImage-to-Text Retrieval+4 tasks
4 papers · 0 benchmarks
MineralImage5k (Benchmark for 5k raw mineral species recognition)
We present a comprehensive dataset comprising a vast collection of raw mineral samples for the purpose of mineral recognition.
ImagesTextsTablesFew-Shot Image ClassificationImage SegmentationZero-Shot Image Classificationregression
1 paper · 0 benchmarks
Omni-Image
Omni-Image is built as a challenging but tractable dataset for continual learning and few-shot learning.
ImagesImage ClassificationFew-Shot Image Classification
1 paper · 0 benchmarks

Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.