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Unsupervised Semantic Segmentation datasets

archive 2025-07-28

9 datasets carry the task tag "Unsupervised Semantic Segmentation" (the task itself: Unsupervised Semantic Segmentation), ordered by the archive's paper count. Page 1 of 1: 9 shown of 9. 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 52Unsupervised Semantic Segmentation 9

Unsupervised Semantic Segmentation datasets 1–9 of 9

COCO (Common Objects in Context)
The COCO (Common Objects in Context) dataset is a large-scale object detection, segmentation, and captioning dataset.
ImagesVideosObject DetectionSemantic SegmentationQuestion AnsweringPose EstimationVisual Question Answering (VQA)Instance Segmentation+54 tasks
11,922 papers · 77 benchmarks
Cityscapes
Cityscapes is a large-scale database which focuses on semantic understanding of urban street scenes.
ImagesSemantic SegmentationImage Generation2D Semantic SegmentationInstance SegmentationScene ParsingImage-to-Image Translation+27 tasks
3,702 papers · 51 benchmarks
COCO-Stuff (Common Objects in COntext-stuff)
The Common Objects in COntext-stuff (COCO-stuff) dataset is a dataset for scene understanding tasks like semantic segmentation, object detection and image captioning.
ImagesSemantic SegmentationImage-to-Image TranslationUnsupervised Semantic SegmentationOpen Vocabulary Semantic SegmentationUnsupervised Semantic Segmentation with Language-image Pre-trainingLayout-to-Image Generation+4 tasks
338 papers · 17 benchmarks
Dark Zurich
Dark Zurich is an image dataset containing a total of 8779 images captured at nighttime, twilight, and daytime, along with the respective GPS coordinates of the camera for each image.
ImagesSemantic SegmentationUnsupervised Semantic SegmentationSource-Free Domain Adaptation
57 papers · 3 benchmarks
ImageNet-S (ImageNet Semantic Segmentation)
Powered by the ImageNet dataset, unsupervised learning on large-scale data has made significant advances for classification tasks.
ImagesSemantic SegmentationSemi-Supervised Semantic SegmentationUnsupervised Semantic SegmentationZero-Shot Transfer Image ClassificationPrompt Engineering
43 papers · 6 benchmarks
SUIM (Segmentation of Underwater IMagery)
The Segmentation of Underwater IMagery (SUIM) dataset contains over 1500 images with pixel annotations for eight object categories: fish (vertebrates), reefs (invertebrates), aquatic plants, wrecks/ruins, human divers, robots, and…
ImagesSemantic SegmentationSemi-Supervised Semantic SegmentationUnsupervised Semantic SegmentationScene UnderstandingSaliency Prediction
34 papers · 2 benchmarks
ACDC (Adverse Conditions Dataset with Correspondences)
We introduce ACDC, the Adverse Conditions Dataset with Correspondences for training and testing semantic segmentation methods on adverse visual conditions.
Domain AdaptationUnsupervised Semantic SegmentationDomain GeneralizationSource-Free Domain AdaptationFoggy Scene Segmentation
31 papers · 5 benchmarks
Nighttime Driving
Nighttime Driving is a dataset of road scenes consisting of 35,000 images ranging from daytime to twilight time and to nighttime.
ImagesSemantic SegmentationUnsupervised Semantic Segmentation
27 papers · 2 benchmarks
KITTI-STEP
The Segmenting and Tracking Every Pixel (STEP) benchmark consists of 21 training sequences and 29 test sequences.
ImagesUnsupervised Semantic SegmentationUnsupervised Semantic Segmentation with Language-image Pre-trainingVideo Panoptic Segmentation
24 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.