| id,fullname,link,license,citation,category,geography,sensor,description,tags |
| C3VD,Colonoscopy 3D Video Dataset,https://durrlab.github.io/C3VD/,CC-BY-NC-SA-3.0,bobrow2023c3vd,Object,-,Clinical colonoscope,Colonoscopy video with registered 3D ground truth captured on a high-fidelity colon phantom.,medical;endoscopy;object-centric |
| DSTORM,dSTORM super-resolution microscopy,,-,vandelinde2011nprot-dstorm,Object,-,dSTORM microscope,Single-molecule localization microscopy point clouds of subcellular structures at nanometre scale.,microscopy;nanoscale;object-centric |
| FRUIT,Fruit completion dataset,https://www.ipb.uni-bonn.de/data/shape_completion/,MIT,magistri2025icra,Object,Germany,"Hand-held scanner, RealSense RGB-D",Scans of sweet pepper plants for fruit shape completion in agricultural robotics.,agriculture;plant-phenotyping;object-centric |
| STANFORD3D,Stanford 3D Scanning Repository,http://graphics.stanford.edu/data/3Dscanrep/,Custom research license,curless1996siggraph,Object,USA,Cyberware laser scanner,"Classic range-scan models (bunny, dragon, happy buddha, armadillo) acquired from multiple viewpoints.",object-centric;range-scan;classic-benchmark |
| UWA3D,UWA 3D Object Dataset,https://dx.doi.org/10.21227/6rgk-8697,Research use only,mian2006pami-uwa,Object,Australia,Minolta Vivid 910,Turntable range scans of four objects from multiple viewpoints; also ships 50 cluttered scenes with object pose ground truth.,object-centric;range-scan;classic-benchmark |
| LANDSLIDESIM,Rockfall Simulator,https://huggingface.co/datasets/zhaoyiww/Rockfall_Simulator,CC-BY-4.0,wang2025arxiv-rockfall,Object,Switzerland,Terrestrial laser scanner and total station,"Simulated rockfall sequence for geomonitoring, captured as multi-epoch terrestrial laser scans with RGB imagery.",geoscience;rockfall;change-detection;multi-epoch;tls |
| 3DCSR,3D Cross-Source dataset,https://multimediauts.org/3D_data_for_registration/,CC-BY-NC-SA-3.0,huang2021arxiv-comprehensive,IndoorScan,USA,"Kinect RGB-D, Velodyne-16 LiDAR, SfM",Cross-source indoor point clouds pairing Kinect RGB-D reconstructions with LiDAR and SfM captures of the same rooms.,indoor;cross-source;rgb-d |
| BONNRGBD,Bonn RGB-D Dynamic Dataset,https://www.ipb.uni-bonn.de/data/rgbd-dynamic-dataset/,CC BY-NC-SA 3.0,palazzolo2019iros,IndoorScan,Germany,ASUS RGB-D camera,"Indoor RGB-D sequences containing moving people, recorded for dynamic SLAM evaluation.",indoor;rgb-d;dynamic-scene |
| IILABS3D,II-LABS-3D,https://rdm.inesctec.pt/dataset/nis-2025-001,CC-BY-SA-4.0,ribeiro2025access,IndoorScan,Portugal,"Livox Mid-360, RoboSense Helios",Indoor mobile-robot LiDAR sequences recorded in a laboratory environment.,indoor;lidar;mobile-robot |
| LEGKILO,Leg-KILO,https://github.com/ouguangjun/legkilo-dataset,CC-BY-4.0,ou2024ral,IndoorScan,China,Livox Mid-360,"LiDAR sequences captured from a legged robot, with strong motion from the walking gait.",legged-robot;lidar;kinematic-odometry |
| MATTERPORT3D,Matterport3D,https://niessner.github.io/Matterport/,Custom research license,chang2017threedv-matterport3d,IndoorScan,USA,Matterport Pro RGB-D camera,"Panoramic RGB-D captures of complete building interiors, covering homes, offices and construction sites.",indoor;rgb-d;building-scale |
| REDWOOD,Redwood augmented ICL-NUIM indoor scenes,http://redwood-data.org/,CC0-1.0,choi2015cvpr,IndoorScan,Synthetic,Simulated RGB-D camera,Synthetic RGB-D reconstructions of living rooms and offices with exact ground-truth geometry.,indoor;synthetic;rgb-d |
| TIERS,TIERS multi-LiDAR dataset,https://github.com/tiers/tiers-lidars-dataset,MIT,sier2023rs-tiers,IndoorScan,Finland,"Velodyne-16, Ouster-64/128, Livox",Indoor and outdoor sequences recorded simultaneously with several heterogeneous LiDARs.,indoor;multi-lidar;heterogeneous-sensor |
| TUMRGBD,TUM RGB-D SLAM Dataset and Benchmark,https://cvg.cit.tum.de/data/datasets/rgbd-dataset,CC-BY-4.0,sturm2012iros,IndoorScan,Germany,Kinect RGB-D camera,Handheld RGB-D sequences of office scenes with motion-capture ground-truth trajectories.,indoor;rgb-d;slam-benchmark |
| RESSO,RESSO,https://3d.bk.tudelft.nl/liangliang/publications/2019/plade/resso.html,-,chen2020tgrs-plade,IndoorScan;TLS,"Netherlands, Saudi Arabia",Leica and Faro TLS,Terrestrial laser scans of building interiors and facades used for plane-based registration.,tls;building;plane-based |
| ARGOVERSE2,Argoverse 2,https://www.argoverse.org/av2.html,CC-BY-NC-SA-4.0,wilson2021neurips,OutdoorScan,USA,2 x 32-beam LiDAR,Urban autonomous-driving sequences recorded with a roof-mounted dual-LiDAR stack.,autonomous-driving;urban;lidar |
| DIGIFOREST,DigiForest,https://www.ipb.uni-bonn.de/data/digiforest-dataset/,CC BY-NC-SA 4.0,malladi2025icra,OutdoorScan,Switzerland,Hesai 32/64-beam LiDAR,Forest submaps recorded by a hand-held and legged-robot LiDAR platform for forestry inventory.,forest;lidar;submap |
| MUSTC,MUST-C,https://www.ipb.uni-bonn.de/data/MuST-C/,CC-BY-4.0,chong2026sdata,OutdoorScan,Germany,"Ouster 128-beam LiDAR, RIEGL scanner",Repeated multi-sensor scans of agricultural crop plots recorded across a growing season.,agriculture;multi-temporal;lidar |
| NCLT,North Campus Long-Term dataset,http://robots.engin.umich.edu/nclt/,ODbL,carlevaris-bianco2016ijrr,OutdoorScan,USA,Velodyne 32-beam LiDAR,Long-term campus sequences recorded by a segway platform over more than a year.,campus;long-term;lidar |
| PANDASET,PandaSet,https://pandaset-git-master.scaleai1.vercel.app/,CC-BY-NC-SA-4.0,xiao2021itsc-pandaset,OutdoorScan,USA,Hesai 64-beam and forward-facing LiDAR,Urban driving sequences combining a spinning 64-beam LiDAR with a solid-state forward LiDAR.,autonomous-driving;urban;lidar |
| SGAB,SGAB,https://arc.nus.edu.sg/project/2020/10/abcd/,Custom research license,chong2022sgab,OutdoorScan,Singapore,3 x Velodyne 16-beam LiDAR,Outdoor mobile scans recorded by a ground vehicle carrying three 16-beam LiDARs.,outdoor;mobile-mapping;lidar |
| SUBT,SubT-MRS,https://theairlab.org/subt-mrs/,CC-BY-4.0,zhao2024cvpr-subt,OutdoorScan,USA,Velodyne 16-beam LiDAR,"Subterranean and degraded-environment sequences from caves, tunnels and urban structures.",subterranean;degraded-environment;lidar |
| TRUCKSCENES,TruckScenes,https://brandportal.man/d/QSf8mPdU5Hgj,CC-BY-NC-SA-4.0,fent2024neurips-truckscenes,OutdoorScan,Germany,6 x LiDAR,Heavy-truck driving sequences recorded with six LiDARs distributed around the vehicle.,autonomous-driving;truck;multi-lidar |
| WAYMO,Waymo Open Dataset,https://waymo.com/open/,Custom research license,sun2020cvpr,OutdoorScan,USA,5 x LiDAR,Large-scale urban and suburban driving sequences with one mid-range and four short-range LiDARs.,autonomous-driving;urban;lidar |
| ZOD,Zenseact Open Dataset,https://zod.zenseact.com/,CC-BY-SA-4.0,alibeigi2023iccv-zod,OutdoorScan,14 European countries,Velodyne 128-beam LiDAR,Driving sequences collected across Europe covering diverse road types and weather.,autonomous-driving;europe;lidar |
| AEVASCENES,AevaScenes,https://scenes.aeva.com/,Academic / non-commercial use,narasimhan2025misc-aevascenes,OutdoorScan,"San Francisco Bay Area, USA","Aeva FMCW 4D LiDAR (6 units: 4 wide FOV, 2 narrow FOV)","Open-access FMCW 4D LiDAR and camera sequences with per-point velocity, recorded across urban and highway driving at ranges up to 400 m.",autonomous-driving;fmcw;lidar;long-range;per-point-velocity |
| CDDREG,CDD: self-built cross-domain point cloud registration dataset,https://doi.org/10.1038/s41597-025-04897-x,CC-BY-4.0,wang2025sdata-cdd,OutdoorScan,China,Terrestrial LiDAR (downward-tilted mounting),"Point cloud registration pairs built with deliberate domain-discrepancy variables via spatial sampling and temporal interval frame matching, for cross-domain generalization research.",cross-domain;registration;generalization;lidar |
| DEBRISFLOW,High-frequency 3D LiDAR measurements of a debris flow,https://doi.org/10.3929/ethz-b-000599948,CC-BY-SA-4.0,aaron2023grl,OutdoorScan,Switzerland,"High-frequency terrestrial LiDAR (10 Hz), calibrated camera","Sub-second 3D laser scans of a full-scale debris flow captured in the field, released to study internal flow dynamics.",geoscience;debris-flow;high-frequency-lidar;change-detection |
| IQMULUS,IQmulus / TerraMobilita,https://data.ign.fr/benchmarks/UrbanAnalysis/,CC-BY-NC-ND-3.0,vallet2015cg-iqmulus,OutdoorScan;TLS,"Paris, France",Mobile laser scanner,Dense mobile laser scans of Parisian streets acquired for urban cartography.,mls;urban;street |
| PARISLUCO,ParisLuco3D,https://npm3d.fr/parisluco3d,CC-BY-NC-ND-3.0,sanchez2023arxiv-parisluco,OutdoorScan,"Paris, France",Mobile laser scanner,"Mobile LiDAR scans of central Paris, released as a high-quality target set for cross-domain LiDAR perception.",mls;urban;street;domain-generalization |
| AHN,Actueel Hoogtebestand Nederland,https://www.ahn.nl/,CC0-1.0,cserep2023jag-ahn,Map,Netherlands,Airborne laser scanning,"National airborne laser scanning of the Netherlands, released in successive nationwide campaigns.",als;national-survey;multi-temporal |
| ALITA,ALITA,https://metaslam.github.io/datasets/alita/,BSD-3-Clause,yin2022arxiv-alita,Map,USA,Map built by Velodyne 16-beam LiDAR,Long-term urban LiDAR maps built for place recognition across repeated traversals.,map;place-recognition;long-term |
| APOLLO,Apollo-SouthBay,https://developer.apollo.auto/southbay.html,Custom research license,huang2018cvprws,Map,USA,Map built by Velodyne 64-beam LiDAR,"Repeated drives through the San Francisco South Bay, released as registered session maps.",map;urban;multi-session |
| EVO,Evo test site ALS (Scanforest),https://doi.org/10.23729/bda72e80-d8c5-4b58-a567-81a19c6a4213,CC-BY-4.0,evo2023als,Map,Finland,Airborne laser scanning (~15 pts/m2),"Two adjacent tiles from the summer 2009 airborne laser scan of the Evo test site in southern Finland, flown at ~15 pts/m2 over 119 forest sample plots and released open access through Scanforest.",als;forest;boreal;open-data |
| KIMERAMULTI,Kimera-Multi dataset,https://web.mit.edu/sparklab/datasets/KimeraMultiData/,MIT,tian2023iros-kimeramultidata,OutdoorScan;Map,USA,Map built by Velodyne 16-beam LiDAR,Multi-robot campus sequences with per-robot maps built during a collaborative SLAM session.,multi-robot;slam;map-merging |
| KITTI,KITTI Vision Benchmark Suite,https://www.cvlibs.net/datasets/kitti/,CC-BY-NC-SA-3.0,geiger2012cvpr,OutdoorScan;Map,"Karlsruhe, Germany",Velodyne 64-beam LiDAR,Urban and highway driving sequences that form the standard outdoor registration benchmark.,autonomous-driving;urban;classic-benchmark |
| KITTI360,KITTI-360,https://www.cvlibs.net/datasets/kitti-360/,CC-BY-NC-SA-3.0,liao2022pami,Map,"Karlsruhe, Germany",Velodyne 64-beam LiDAR,Suburban driving sequences recorded around Karlsruhe with dense 360-degree annotation.,autonomous-driving;suburban;lidar |
| MSD,MS-Mapping (MS-HKUSTGZ),https://github.com/JokerJohn/MS-Mapping,-,hu2024arxiv-msmapping,Map,"Guangzhou, China",Map built by HESAI 32-beam LiDAR,Multi-session campus maps built incrementally over repeated visits to the HKUST(GZ) campus.,map;multi-session;campus |
| MULRAN,MulRAN,https://sites.google.com/view/mulran-pr,CC BY-NC-SA 4.0,kim2020icra,Map,South Korea,Map built by Ouster 64-beam LiDAR,Multimodal range sequences revisiting the same urban and campus sites over many months.,map;place-recognition;multi-session |
| STHEREO,STheReO,https://sites.google.com/view/rpmsthereo/,-,,Map,South Korea,Map built by Ouster 64-beam LiDAR,Multi-spectral stereo and LiDAR sequences recorded on the KAIST campus.,map;campus;multi-session |
| HELIPR,HeLiPR,https://sites.google.com/view/heliprdataset,CC BY-NC-SA 4.0,jung2024ijrr,OutdoorScan;Map,South Korea,"Ouster-128, Livox Avia, Aeva FMCW, Velodyne-16",The same routes recorded simultaneously by four heterogeneous LiDARs across seasons.,heterogeneous-lidar;place-recognition;multi-session |
| ABENBERG,Abenberg airborne laser scanning,https://www.asg.ed.tum.de/pf/publications/test-datasets/,CC-BY-NC-SA-4.0,hebel2013jprs,Map,"Abenberg, Germany",Airborne laser scanning,Repeated airborne laser scans of a rural town acquired for change detection.,als;rural;change-detection |
| LYONSYN,Lyon synthetic airborne laser scanning,https://ieee-dataport.org/open-access/urb3dcd-urban-point-clouds-simulated-dataset-3d-change-detection,-,degelis2021rs-urb3dcd,Map,"Lyon, France",Simulated airborne laser scanning,Simulated airborne laser scans of an urban district under varying flight configurations.,als;synthetic;urban |
| TORONTOALS,Toronto airborne laser scanning strips,,-,,Map,"Toronto, Canada",Airborne laser scanning,Overlapping airborne laser scanning strips flown over downtown Toronto.,als;urban;strip-adjustment |
| ETH3D,ETH3D,https://www.eth3d.net/,CC-BY-NC-SA-4.0,schops2017cvpr-eth3d,IndoorScan;TLS,"Zurich, Switzerland",Leica TLS,High-resolution laser scans of indoor and outdoor scenes released as a multi-view stereo benchmark.,tls;multi-view-stereo;benchmark |
| ETHPRS,ETH-TLS (ETH Zurich PRS),https://prs.igp.ethz.ch/research/completed_projects/automatic_registration_of_point_clouds.html,-,theiler2015jprs,TLS,"Zurich, Switzerland",Terrestrial laser scanner,Terrestrial laser scans of buildings and vegetation used for marker-free registration research.,tls;registration;outdoor |
| INDOORLRS,Indoor LiDAR-RGBD scan dataset,http://redwood-data.org/indoor_lidar_rgbd/,CC0-1.0,park2017iccv,TLS,-,"Faro TLS, ASUS RGB-D camera",Furnished indoor rooms captured by both a Faro laser scanner and an RGB-D camera.,tls;indoor;rgb-d |
| MCD,MCD (Multi-Campus Dataset),https://mcdviral.github.io/,CC-BY-NC-SA-4.0,nguyen2024cvpr-mcd,TLS,"Sweden, Germany, Singapore",Leica and Faro TLS,"Survey-grade laser scans of three university campuses, released as ground truth for SLAM.",tls;campus;survey-grade |
| OXFORDSPIRES,Oxford Spires,https://dynamic.robots.ox.ac.uk/datasets/oxford-spires/,-,tao2025ijrr-oxfordspires,TLS,"Oxford, UK",Leica TLS,Survey-grade laser scans of Oxford colleges and landmarks used as SLAM ground truth.,tls;heritage;campus |
| R3DS,Robotic 3D Scan Repository,http://kos.informatik.uni-osnabrueck.de/3Dscans/,-,nuchter2009r3ds,TLS,"Germany, Croatia",Riegl TLS,Terrestrial laser scans of city centres and rescue training sites collected for robotic mapping.,tls;urban;robotics |
| SEM3D,Semantic3D,http://www.semantic3d.net/,CC-BY-NC-SA-3.0,hackel2017isprs,TLS,Switzerland,Terrestrial laser scanner,Large static terrestrial scans of European village and city scenes with semantic labels.,tls;semantic-segmentation;urban |
| TJTREE,Tongji-Trees,https://github.com/zexinyang/GlobalMatch,Apache-2.0,wang2023jprs-globalmatch,TLS,"Shanghai, China",Z+F TLS,Terrestrial laser scans of forest plots used for tree-based registration.,tls;forest;tree-mapping |
| TUMTLS,TUM terrestrial laser scanning,https://tum2t.win/datasets,CC-BY-4.0,wysocki2025arxiv-tum2twin,TLS,"Munich, Germany",Terrestrial laser scanner,Terrestrial laser scans of the Munich city centre.,tls;urban;heritage |
| TUMMLS,TUM mobile laser scanning,https://www.asg.ed.tum.de/pf/publications/test-datasets/,-,,TLS,"Munich, Germany",Mobile laser scanner,Mobile laser scans of Munich streets.,mls;urban;street |
| TUMUAS,TUM unmanned aerial system photogrammetry,https://tum2t.win/datasets,CC-BY-4.0,wysocki2025arxiv-tum2twin,TLS,"Munich, Germany",Photogrammetry,"Drone photogrammetric reconstruction of a section of the Munich city centre, co-located with the TUM terrestrial and mobile laser scans.",uas;photogrammetry;urban |
| VMML,VMML (Visualization and MultiMedia Lab),https://www.ifi.uzh.ch/en/vmml/research/datasets.html,Research use only,michailidis2019vc-aspire,TLS,Switzerland,Faro TLS,Terrestrial laser scans of interiors and small buildings captured for architectural reconstruction.,tls;indoor;architecture |
| WHUTLS,WHU-TLS,https://www.isprs.org/resources/datasets/benchmarks/WHU-TLS/default.aspx,CC BY-NC 4.0,dong2020jprs-whutls,TLS,China,RIEGL TLS,"Terrestrial laser scans spanning campus, park, heritage, forest, railway, tunnel and subway scenes.",tls;multi-scenario;registration-benchmark |
| LYFT,Lyft Level 5 Perception Dataset,https://level5.lyft.com/dataset/,CC-BY-NC-SA-4.0,kesten2019lyft,OutdoorScan,"Palo Alto, USA",Roof 64-beam and 2 x bumper 40-beam LiDAR,Urban autonomous-driving sequences recorded in Palo Alto with a roof-mounted 64-beam LiDAR and two bumper-mounted 40-beam LiDARs.,autonomous-driving;urban;lidar |
| HILTI21,Hilti 2021 SLAM Challenge Dataset,https://hilti-challenge.com/dataset-2021,CC BY-NC-SA 3.0,helmberger2022ral,IndoorScan,"Switzerland, Liechtenstein",Ouster OS0-64 LiDAR,"Handheld multi-sensor sequences of construction and laboratory interiors, released with survey-grade ground truth for the Hilti SLAM Challenge.",indoor;handheld;lidar;slam-benchmark |
| FUSIONPORTABLE2,FusionPortable v2,https://fusionportable.github.io/dataset/fusionportable_v2/,CC-BY-NC-SA-3.0,wei2025ijrr-fusionportablev2,IndoorScan,Hong Kong,Ouster OS1-128 LiDAR,"Multi-platform sequences (handheld, legged robot, ground vehicle) recorded across campus, park and indoor environments with a 128-beam LiDAR.",multi-platform;lidar;slam;campus |
| NUPLAN,nuPlan,https://www.nuscenes.org/nuplan,CC-BY-NC-SA-4.0,caesar2021arxiv-nuplan,OutdoorScan,"USA, Singapore",5 x LiDAR,"Large-scale closed-loop planning benchmark for autonomous driving, with LiDAR sweeps recorded across four cities.",autonomous-driving;urban;lidar;planning |
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