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Zero-Shot Learning datasets

archive 2025-07-28

43 datasets carry the task tag "Zero-Shot Learning" (the task itself: Zero-Shot Learning), ordered by the archive's paper count. Page 1 of 1: 43 shown of 43. 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.

Zero-Shot Learning datasets 1–43 of 43

CIFAR-10

description withheld: archive row vandalised before snapshot

Images Image Classification Classification Image Generation Zero-Shot Learning Anomaly Detection Image Retrieval+58 tasks

16,145 papers · 91 benchmarks

ImageNet

The ImageNet dataset contains 14,197,122 annotated images according to the WordNet hierarchy.

Images Image Classification Classification Image Generation Zero-Shot Learning Visual 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.

Images Image Classification Classification Image Generation Zero-Shot Learning Anomaly Detection Few-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.

Images Image Classification Image Generation Zero-Shot Learning Few-Shot Image Classification Image Retrieval Few-Shot Learning+29 tasks

2,235 papers · 47 benchmarks

UCF101 (UCF101 Human Actions dataset)

UCF101 dataset is an extension of UCF50 and consists of 13,320 video clips, which are classified into 101 categories.

Videos Zero-Shot Learning Action Recognition Temporal Action Localization Few-Shot Learning Image Clustering Skeleton Based Action Recognition+16 tasks

1,863 papers · 23 benchmarks

Oxford 102 Flower (102 Category Flower Dataset)

Oxford 102 Flower is an image classification dataset consisting of 102 flower categories.

Images Image Classification Image Generation Zero-Shot Learning Few-Shot Image Classification Few-Shot Learning Continual Learning+10 tasks

1,307 papers · 16 benchmarks

DTD (Describable Textures Dataset)

The Describable Textures Dataset (DTD) contains 5640 texture images in the wild.

Images Image Classification Classification Zero-Shot Learning Few-Shot Learning Image Clustering Neural Architecture Search+3 tasks

870 papers · 8 benchmarks

Food-101

The Food-101 dataset consists of 101 food categories with 750 training and 250 test images per category, making a total of 101k images.

Images Image Classification Classification Zero-Shot Learning Few-Shot Learning Image Clustering Fine-Grained Image Classification+10 tasks

805 papers · 14 benchmarks

Stanford Cars

The Stanford Cars dataset consists of 196 classes of cars with a total of 16,185 images, taken from the rear.

Images Image Classification Image Generation Zero-Shot Learning Few-Shot Image Classification Few-Shot Learning Continual Learning+7 tasks

790 papers · 13 benchmarks

Caltech-101

The Caltech101 dataset contains images from 101 object categories (e.g., “helicopter”, “elephant” and “chair” etc.) and a background category that contains the images not from the 101 object categories.

Images Zero-Shot Learning Semi-Supervised Image Classification Image Clustering Fine-Grained Image Classification Unsupervised Anomaly Detection Transductive Zero-Shot Classification+3 tasks

709 papers · 10 benchmarks

EuroSAT

Eurosat is a dataset and deep learning benchmark for land use and land cover classification.

Images Image Classification Classification Semantic Segmentation Zero-Shot Learning Few-Shot Learning Image Clustering+4 tasks

687 papers · 8 benchmarks

FGVC-Aircraft

FGVC-Aircraft contains 10,200 images of aircraft, with 100 images for each of 102 different aircraft model variants, most of which are airplanes.

Images Image Classification Zero-Shot Learning Few-Shot Learning Image Clustering Fine-Grained Image Classification Neural Architecture Search+5 tasks

520 papers · 12 benchmarks

PASCAL Context

The PASCAL Context dataset is an extension of the PASCAL VOC 2010 detection challenge, and it contains pixel-wise labels for all training images.

Images Semantic Segmentation Zero-Shot Learning Saliency Detection Boundary Detection Surface Normals Estimation Human Parsing

323 papers · 6 benchmarks

AwA (Animals with Attributes)

Animals with Attributes (AwA) was a dataset for benchmarking transfer-learning algorithms, in particular attribute base classification.

Images Zero-Shot Learning Few-Shot Image Classification Generalized Few-Shot Learning Generalized Zero-Shot Learning Concept-based Classification Long-tail learning with class descriptors

264 papers · 3 benchmarks

SNIPS (SNIPS Natural Language Understanding benchmark)

The SNIPS Natural Language Understanding benchmark is a dataset of over 16,000 crowdsourced queries distributed among 7 user intents of various complexity: SearchCreativeWork (e.g.

Texts Zero-Shot Learning Intent Detection Slot Filling Open Intent Discovery Out of Distribution (OOD) Detection Intent Discovery

256 papers · 6 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.

Images Zero-Shot Learning Few-Shot Image Classification Generalized Few-Shot Learning Generalized Zero-Shot Learning Concept-based Classification

231 papers · 5 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).

Images Zero-Shot Learning Few-Shot Image Classification Generalized Zero-Shot Learning Concept-based Classification

147 papers · 5 benchmarks

TVQA

The TVQA dataset is a large-scale video dataset for video question answering.

Videos Texts Zero-Shot Learning Video Question Answering Zero-Shot Video Question Answer

146 papers · 3 benchmarks

LSMDC (Large Scale Movie Description Challenge)

This dataset contains 118,081 short video clips extracted from 202 movies.

Videos Texts Audio Zero-Shot Learning Video Retrieval Zero-Shot Video Retrieval Fill Mask

126 papers · 3 benchmarks

MIT-States

The MIT-States dataset has 245 object classes, 115 attribute classes and ∼53K images.

Images Zero-Shot Learning Image Retrieval with Multi-Modal Query Compositional Zero-Shot Learning

91 papers · 4 benchmarks

MSRVTT-QA

The MSR-VTT-QA dataset is a benchmark for the task of Visual Question Answering (VQA) on the MSR-VTT (Microsoft Research Video to Text) dataset.

Zero-Shot Learning Visual Question Answering (VQA)Visual Question Answering Video Question Answering Zero-Shot Video Question Answer Zeroshot Video Question Answer

66 papers · 5 benchmarks

MSVD-QA

The MSVD-QA dataset is a Video Question Answering (VideoQA) dataset.

Zero-Shot Learning Visual Question Answering (VQA)Visual Question Answering Video Question Answering Zero-Shot Video Question Answer Zeroshot Video Question Answer

61 papers · 5 benchmarks

TVQA+

TVQA+ contains 310.8K bounding boxes, linking depicted objects to visual concepts in questions and answers.

Videos Texts Question Answering Zero-Shot Learning Visual Question Answering (VQA)Video Question Answering Zero-Shot Video Question Answer

60 papers · 0 benchmarks

Oxford-IIIT Pets

The Oxford-IIIT Pet Dataset is a 37-category pet dataset with roughly 200 images for each class.

Image Classification Zero-Shot Learning Image Clustering Fine-Grained Image Classification Neural Architecture Search Transductive Zero-Shot Classification+2 tasks

59 papers · 5 benchmarks

SUN397

The Scene UNderstanding (SUN) database contains 899 categories and 130,519 images.

Images Image Classification Zero-Shot Learning Few-Shot Learning Image Clustering Fine-Grained Image Classification Transductive Zero-Shot Classification+3 tasks

52 papers · 8 benchmarks

OCNLI (Original Chinese Natural Language Inference)

OCNLI stands for Original Chinese Natural Language Inference.

Texts Zero-Shot Learning Language Modelling Natural Language Inference Natural Language Inference (Zero-Shot)Natural Language Inference (One-Shot)Natural Language Inference (Few-Shot)

44 papers · 0 benchmarks

SUN Attribute

The SUN Attribute dataset consists of 14,340 images from 717 scene categories, and each category is annotated with a taxonomy of 102 discriminate attributes.

Images Image Classification Zero-Shot Learning Object Recognition Generalized Zero-Shot Learning

38 papers · 2 benchmarks

How2QA

To collect How2QA for video QA task, the same set of selected video clips are presented to another group of AMT workers for multichoice QA annotation.

Videos Texts Zero-Shot Learning Video Question Answering Video Retrieval Video Captioning

28 papers · 2 benchmarks

EURLEX57K

EURLEX57K is a new publicly available legal LMTC dataset, dubbed EURLEX57K, containing 57k English EU legislative documents from the EUR-LEX portal, tagged with ∼4.3k labels (concepts) from the European Vocabulary (EUROVOC).

Texts Text Classification Zero-Shot Learning Multi-Label Text Classification Hierarchical Multi-label Classification Multilabel Text Classification

23 papers · 1 benchmark

iVQA (Instructional Video Question Answering)

An open-ended VideoQA benchmark that aims to: i) provide a well-defined evaluation by including five correct answer annotations per question and ii) avoid questions which can be answered without the video.

Videos Texts Zero-Shot Learning Visual Question Answering (VQA)Video Question Answering

22 papers · 2 benchmarks

MedConceptsQA

MedConceptsQA - Open Source Medical Concepts QA Benchmark The benchmark can be found here: https://huggingface.co/datasets/ofir408/MedConceptsQA

Texts Question Answering Zero-Shot Learning Few-Shot Learning Large Language Model Medical Diagnosis Medical Procedure

13 papers · 2 benchmarks

COCO-MLT

The COCO-MLT is created from MS COCO-2017, containing 1,909 images from 80 classes.

Images Zero-Shot Learning Long-tail Learning Multi-Label Image Classification

12 papers · 2 benchmarks

VOC-MLT

We construct the long-tailed version of VOC from its 2012 train-val set.

Images Zero-Shot Learning Long-tail Learning Multi-Label Image Classification

12 papers · 2 benchmarks

LAD (Large-scale Attribute Dataset)

LAD (Large-scale Attribute Dataset) has 78,017 images of 5 super-classes and 230 classes.

Images Zero-Shot Learning

10 papers · 0 benchmarks

AO-CLEVr

AO-CLEVr is a new synthetic-images dataset containing images of "easy" Attribute-Object categories, based on the CLEVr.

Images Zero-Shot Learning Compositional Zero-Shot Learning

6 papers · 0 benchmarks

Tasty Videos

A collection of 2511 recipes for zero-shot learning, recognition and anticipation.

Videos Texts Zero-Shot Learning

5 papers · 0 benchmarks

ImageNet_CN (Chinese ImageNet Classification)

transform the ImageNet-1K classification datatset for Chinese models by translating labels and prompts into Chinese.

Images Zero-Shot Learning Zero-Shot Cross-Modal Retrieval Zero-shot Classification (unified classes)

3 papers · 1 benchmark

XL-R2R (Cross-lingual Room-to-Room)

The XL-R2R dataset is built upon the R2R dataset and extends it with Chinese instructions.

Texts Zero-Shot Learning Domain Adaptation Vision-Language Navigation

2 papers · 0 benchmarks

Edge-Map-345C

Edge-Map-345C is a large-scale edge-map dataset including 290,281 edge-maps corresponding to 345 object categories of QuickDraw dataset.

Images Zero-Shot Learning Learning Semantic Representations

1 paper · 0 benchmarks

GOZ (Generic Object ZSL Dataset)

The Generix Object Zero-shot Learning (GOZ) dataset is a benchmark dataset for zero-shot learning.

Images Zero-Shot Learning Object Recognition

1 paper · 0 benchmarks

PubChem18 (PubChem 2018)

A.2.1 AN OPEN, LARGE-SCALE DATASET FOR ZERO-SHOT DRUG DISCOVERY DERIVED FROM PUBCHEM We constructed a large public dataset extracted from PubChem (Kim et al., 2019; Preuer et al., 2018), an open chemistry database, and the largest…

Texts Biology Zero-Shot Learning Molecular Property Prediction Molecular Property Prediction (1-shot))

1 paper · 0 benchmarks

Sequence Consistency Evaluation (SCE) tests

Sequence Consistency Evaluation (SCE) consists of a benchmark task for sequence consistency evaluation (SCE).

Images Time series Zero-Shot Learning Visual Reasoning Relational Reasoning

1 paper · 0 benchmarks

Events classification - Biotech news

A dataset specifically tailored to the biotech news sector, aiming to transcend the limitations of existing benchmarks.

Texts Text Classification Zero-Shot Learning Few-Shot Learning Few-Shot Text Classification Zero-Shot Text Classification

0 papers · 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.

Zero-Shot Learning datasets

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

Zero-Shot Learning datasets 1–43 of 43