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3D Semantic Segmentation datasets
archive 2025-07-2841 datasets carry the task tag "3D Semantic Segmentation" (the task itself: 3D Semantic Segmentation), ordered by the archive's paper count. Page 1 of 1: 41 shown of 41. 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 523D Semantic Segmentation 41
3D Semantic Segmentation datasets 1–41 of 41
The nuScenes dataset is a large-scale autonomous driving dataset.
2,139 papers · 21 benchmarks
SemanticKITTI is a large-scale outdoor-scene dataset for point cloud semantic segmentation.
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.
488 papers · 9 benchmarks
The Waymo Open Dataset is comprised of high resolution sensor data collected by autonomous vehicles operated by the Waymo Driver in a wide variety of conditions.
481 papers · 16 benchmarks
KITTI-360 is a large-scale dataset that contains rich sensory information and full annotations.
246 papers · 7 benchmarks
PartNet is a consistent, large-scale dataset of 3D objects annotated with fine-grained, instance-level, and hierarchical 3D part information.
156 papers · 3 benchmarks
For many fundamental scene understanding tasks, it is difficult or impossible to obtain per-pixel ground truth labels from real images.
108 papers · 4 benchmarks
Despite the considerable progress in automatic abdominal multi-organ segmentation from CT/MRI scans in recent years, a comprehensive evaluation of the models' capabilities is hampered by the lack of a large-scale benchmark from diverse…
105 papers · 1 benchmark
The SemanticPOSS dataset for 3D semantic segmentation contains 2988 various and complicated LiDAR scans with large quantity of dynamic instances.
71 papers · 1 benchmark
RELLIS-3D is a multi-modal dataset for off-road robotics.
57 papers · 3 benchmarks
The ScanNet200 benchmark studies 200-class 3D semantic segmentation - an order of magnitude more class categories than previous 3D scene understanding benchmarks.
45 papers · 3 benchmarks
A novel dataset and benchmark, which features 1482 RGB-D scans of 478 environments across multiple time steps.
44 papers · 4 benchmarks
Our project (STPLS3D) aims to provide a large-scale aerial photogrammetry dataset with synthetic and real annotated 3D point clouds for semantic and instance segmentation tasks.
36 papers · 3 benchmarks
🤖 Robo3D - The nuScenes-C Benchmark nuScenes-C is an evaluation benchmark heading toward robust and reliable 3D perception in autonomous driving.
33 papers · 2 benchmarks
The SensatUrbat dataset is an urban-scale photogrammetric point cloud dataset with nearly three billion richly annotated points, which is five times the number of labeled points than the existing largest point cloud dataset.
28 papers · 1 benchmark
DALES (DALES: A Large-scale Aerial LiDAR Data Set for Semantic Segmentation)
We present the Dayton Annotated LiDAR Earth Scan (DALES) data set, a new large-scale aerial LiDAR data set with over a half-billion hand-labeled points spanning 10 square kilometers of area and eight object categories.
26 papers · 2 benchmarks
🤖 Robo3D - The SemanticKITTI-C Benchmark SemanticKITTI-C is an evaluation benchmark heading toward robust and reliable 3D semantic segmentation in autonomous driving.
26 papers · 1 benchmark
ScanNet++ (ScanNet++: A High-Fidelity Dataset of 3D Indoor Scenes)
ScanNet++ is a large scale dataset with 450+ 3D indoor scenes containing sub-millimeter resolution laser scans, registered 33-megapixel DSLR images, and commodity RGB-D streams from iPhone.
25 papers · 5 benchmarks
Toronto-3D is a large-scale urban outdoor point cloud dataset acquired by an MLS system in Toronto, Canada for semantic segmentation.
24 papers · 2 benchmarks
SynLiDAR is a large-scale synthetic LiDAR sequential point cloud dataset with point-wise annotations.
20 papers · 1 benchmark
ScribbleKITTI is a scribble-annotated dataset for LiDAR semantic segmentation.
19 papers · 2 benchmarks
The Paris-Lille-3D is a Benchmark on Point Cloud Classification.
15 papers · 1 benchmark
The Habitat-Matterport 3D Semantics Dataset (HM3DSem) is the largest-ever dataset of 3D real-world and indoor spaces with densely annotated semantics that is available to the academic community.
13 papers · 0 benchmarks
SemanticSTF is an adverse-weather point cloud dataset that provides dense point-level annotations and allows to study 3DSS under various adverse weather conditions.
12 papers · 1 benchmark
WildScenes is a bi-modal benchmark dataset consisting of multiple large-scale, sequential traversals in natural environments, including semantic annotations in high-resolution 2D images and dense 3D LiDAR point clouds, and accurate 6-DoF…
12 papers · 2 benchmarks
BuildingNet is a large-scale dataset of 3D building models whose exteriors are consistently labeled.
11 papers · 0 benchmarks
Are current 3D object tracking methods truely robust enough for low-fidelity depth sensors like the iPhone LiDAR?
8 papers · 2 benchmarks
FOR-instance (FOR-instance: a UAV laser scanning benchmark dataset for semantic and instance segmentation of individual trees)
The challenge of accurately segmenting individual trees from laser scanning data hinders the assessment of crucial tree parameters necessary for effective forest management, impacting many downstream applications.
7 papers · 0 benchmarks
KiTS19 (The 2019 Kidney and Kidney Tumor Segmentation Challenge)
The 2021 Kidney and Kidney Tumor Segmentation challenge (abbreviated KiTS21) is a competition in which teams compete to develop the best system for automatic semantic segmentation of renal tumors and surrounding anatomy.
7 papers · 1 benchmark
LiDAR-MOS (LiDAR-based Moving Object Segmentation)
Tasks.
6 papers · 0 benchmarks
🤖 Robo3D - The WOD-C Benchmark WOD-C is an evaluation benchmark heading toward robust and reliable 3D perception in autonomous driving.
5 papers · 1 benchmark
Swiss3DCities is a dataset that is manually annotated for semantic segmentation with per-point labels, and is built using photogrammetry from images acquired by multirotors equipped with high-resolution cameras.
4 papers · 0 benchmarks
ARCH2S (Dataset, Benchmark for Learning Exterior Architectural Structures from Point Clouds)
Precise segmentation of architectural structures provides detailed information about various building components, enhancing our understanding and interaction with our built environment.
3 papers · 1 benchmark
OpenTrench3D, the first publicly available point cloud dataset of underground utilities from open trenches.
3 papers · 1 benchmark
3D Platelet EM (Platelet Electron Microscopy)
The platelet-em dataset contains two 3D scanning electron microscope (EM) images of human platelets, as well as instance and semantic segmentations of those two image volumes.
2 papers · 2 benchmarks
We complement ARKitScenes dataset with dense semantic annotations that are automatically generated at scale.
1 paper · 0 benchmarks
ECLAIR (ECLAIR: A High-Fidelity Aerial LiDAR Dataset for Semantic Segmentation)
ECLAIR (Extended Classification of Lidar for AI Recognition), a new outdoor large-scale aerial LiDAR dataset designed specifically for advancing research in point cloud semantic segmentation.
1 paper · 1 benchmark
GF-PA66 3D XCT (Glass fiber-reinforced polyamide 66 (GF-PA66) 3D X-ray Computed Tomography (XCT)))
Stack of 2D gray images of glass fiber-reinforced polyamide 66 (GF-PA66) 3D X-ray Computed Tomography (XCT) specimen.
1 paper · 1 benchmark
GF-PA66 3D XCT (latest) (Glass fiber-reinforced polyamide 66 3D X-ray Computed Tomography)
Stack of 2D gray images of glass fiber-reinforced polyamide 66 (GF-PA66) 3D X-ray Computed Tomography (XCT) specimen.
1 paper · 0 benchmarks
Heritage Pointcloud Instance Collection dataset, acquired from two large buildings and annotated at a point-wise semantic level based on existent BIM models.
1 paper · 1 benchmark
InLUT3D (Indoor Lodz University of Technology Point Cloud Dataset)
This dataset called Indoor Lodz University of Technology Point Cloud Dataset (InLUT3D) is a point cloud set tailored for real object classification and both semantic and instance segmentation tasks.
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.