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Generalized Zero-Shot Learning datasets

archive 2025-07-28

10 datasets carry the task tag "Generalized Zero-Shot Learning" (the task itself: Generalized Zero-Shot Learning), ordered by the archive's paper count. Page 1 of 1: 10 shown of 10. 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 52Generalized Zero-Shot Learning 10

Generalized Zero-Shot Learning datasets 1–10 of 10

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
ScanNet
ScanNet is an instance-level indoor RGB-D dataset that includes both 2D and 3D data.
ImagesRGB-DSemantic Segmentation3D Object DetectionDepth Estimation3D ReconstructionPanoptic SegmentationScene Segmentation+11 tasks
1,595 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
SemanticKITTI
SemanticKITTI is a large-scale outdoor-scene dataset for point cloud semantic segmentation.
LiDARSemi-Supervised Semantic SegmentationPanoptic Segmentation3D Semantic SegmentationGeneralized Zero-Shot Learning3D Semantic Scene CompletionLIDAR Semantic Segmentation+5 tasks
669 papers · 10 benchmarks
S3DIS (Stanford 3D Indoor Scene Dataset (S3DIS))
The Stanford 3D Indoor Scene Dataset (S3DIS) dataset contains 6 large-scale indoor areas with 271 rooms.
3DPoint cloudSemantic Segmentation3D Object DetectionPanoptic Segmentation3D Semantic SegmentationGeneralized Zero-Shot Learning3D Instance Segmentation+2 tasks
488 papers · 9 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
OntoNotes 5.0
OntoNotes 5.0 is a large corpus comprising various genres of text (news, conversational telephone speech, weblogs, usenet newsgroups, broadcast, talk shows) in three languages (English, Chinese, and Arabic) with structural information…
TextsNamed Entity Recognition (NER)UIECoreference ResolutionGeneralized Zero-Shot LearningSemantic Role LabelingNamed Entity Recognition+5 tasks
254 papers · 12 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
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
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.
ImagesImage ClassificationZero-Shot LearningObject RecognitionGeneralized Zero-Shot Learning
38 papers · 2 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.