mlsanityData to 7 Oct 2026

Paris-CARLA-3D: A Real and Synthetic Outdoor Point Cloud Dataset for Challenging Tasks in 3D Mapping

arXiv 2111.11348 ↗First posted 22 Nov 2021cs.CV cs.AI cs.ROcited by 25

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Abstract (arXiv)

Paris-CARLA-3D is a dataset of several dense colored point clouds of outdoor environments built by a mobile LiDAR and camera system. The data are composed of two sets with synthetic data from the open source CARLA simulator (700 million points) and real data acquired in the city of Paris (60 million points), hence the name Paris-CARLA-3D. One of the advantages of this dataset is to have simulated the same LiDAR and camera platform in the open source CARLA simulator as the one used to produce the real data. In addition, manual annotation of the classes using the semantic tags of CARLA was performed on the real data, allowing the testing of transfer methods from the synthetic to the real data. The objective of this dataset is to provide a challenging dataset to evaluate and improve methods on difficult vision tasks for the 3D mapping of outdoor environments: semantic segmentation, instance segmentation, and scene completion. For each task, we describe the evaluation protocol as well as the experiments carried out to establish a baseline.

Key facts. Cited by 25 papers in the map (data through 7 Oct 2026). Builds on 27 of its 47 references that are in the map. First posted on arXiv 22 Nov 2021.

Builds on

27 of 47 references.

References · 27

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,485
  3. 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,384
  4. 2017ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenescited by 3,088
  5. 2017CARLA: An Open Urban Driving Simulatorcited by 2,431
  6. 2017Matterport3D: Learning from RGB-D Data in Indoor Environmentscited by 1,354
  7. 2019KPConv: Flexible and Deformable Convolution for Point Cloudscited by 1,202
  8. 2018Panoptic Segmentationcited by 796
  9. 2019Deep Learning for 3D Point Clouds: A Surveycited by 557
  10. 2020A2D2: Audi Autonomous Driving Datasetcited by 189
  11. 2017Semantic3D.net: A new Large-scale Point Cloud Classification Benchmarkcited by 158
  12. 2020SemanticPOSS: A Point Cloud Dataset with Large Quantity of Dynamic Instancescited by 123
15 more
  1. 2019Depth Completion from Sparse LiDAR Data with Depth-Normal Constraintscited by 108
  2. 2020Towards Semantic Segmentation of Urban-Scale 3D Point Clouds: A Dataset, Benchmarks and Challengescited by 80
  3. 2019SG-NN: Sparse Generative Neural Networks for Self-Supervised Scene Completion of RGB-D Scanscited by 77
  4. 2020Toronto-3D: A Large-scale Mobile LiDAR Dataset for Semantic Segmentation of Urban Roadwayscited by 77
  5. 20213D Semantic Scene Completion: a Surveycited by 74
  6. 2017Paris-Lille-3D: a large and high-quality ground truth urban point cloud dataset for automatic segmentation and classificationcited by 65
  7. 2020DALES: A Large-scale Aerial LiDAR Data Set for Semantic Segmentationcited by 65
  8. 2018IMLS-SLAM: scan-to-model matching based on 3D datacited by 40
  9. 2020SPSG: Self-Supervised Photometric Scene Generation from RGB-D Scanscited by 34
  10. 2021KITTI-CARLA: a KITTI-like dataset generated by CARLA Simulatorcited by 33
  11. 2019Precise Synthetic Image and LiDAR (PreSIL) Dataset for Autonomous Vehicle Perceptioncited by 29
  12. 2020Review: deep learning on 3D point cloudscited by 29
  13. 2020Campus3D: A Photogrammetry Point Cloud Benchmark for Hierarchical Understanding of Outdoor Scenecited by 27
  14. 2019SynthCity: A large scale synthetic point cloudcited by 26
  15. 2020Torch-Points3D: A Modular Multi-Task Frameworkfor Reproducible Deep Learning on 3D Point Cloudscited by 23

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 7; 2023: 4; 2024: 4; 2025: 8; 2026: 2.

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  1. 2023Synthesizing Diverse Human Motions in 3D Indoor Scenescited by 109
  2. 2022MotionSC: Data Set and Network for Real-Time Semantic Mapping in Dynamic Environmentscited by 40
  3. 2025AerialMegaDepth: Learning Aerial-Ground Reconstruction and View Synthesiscited by 39
  4. 2022PD-Flow: A Point Cloud Denoising Framework with Normalizing Flowscited by 19
  5. 2022Synthehicle: Multi-Vehicle Multi-Camera Tracking in Virtual Citiescited by 12
  6. 2024MeshVPR: Citywide Visual Place Recognition Using 3D Meshescited by 8
  7. 2022Real-Time Multi-Modal Semantic Fusion on Unmanned Aerial Vehicles with Label Propagation for Cross-Domain Adaptationcited by 6
  8. 2024Deep Learning on 3D Semantic Segmentation: A Detailed Reviewcited by 6
  9. 2023TUM-FAcCADE: Reviewing and enriching point cloud benchmarks for faccade segmentationcited by 5
  10. 2025TUM2TWIN: Introducing the Large-Scale Multimodal Urban Digital Twin Benchmark Datasetcited by 5
  11. 2022IBISCape: A Simulated Benchmark for multi-modal SLAM Systems Evaluation in Large-scale Dynamic Environmentscited by 3
  12. 2024ZAHA: Introducing the Level of Facade Generalization and the Large-Scale Point Cloud Facade Semantic Segmentation Benchmark Datasetcited by 3
13 more
  1. 2025Synth It Like KITTI: Synthetic Data Generation for Object Detection in Driving Scenarioscited by 3
  2. 2025TrueCity: Real and Simulated Urban Data for Cross-Domain 3D Scene Understandingcited by 2
  3. 2022Unsigned Distance Field as an Accurate 3D Scene Representation for Neural Scene Completioncited by 1
  4. 2025Mind the Domain Gap: Measuring the Domain Gap Between Real-World and Synthetic Point Clouds for Automated Driving Developmentcited by 1
  5. 2026PRISM: Color-Stratified Point Cloud Samplingcited by 1
  6. 2026UnderOneFacade: Worldwide Facade Semantic Segmentation Benchmark Datasetcited by 1
  7. 2022Simulation-to-Reality domain adaptation for offline 3D object annotation on pointclouds with correlation alignmentcited by 0
  8. 2023Single-Shot Global Localization via Graph-Theoretic Correspondence Matchingcited by 0
  9. 2023Randomized 3D Scene Generation for Generalizable Self-Supervised Pre-Trainingcited by 0
  10. 2024WHU-Synthetic: A Synthetic Perception Dataset for 3-D Multitask Model Researchcited by 0
  11. 2025Omnidirectional Depth-Aided Occupancy Prediction based on Cylindrical Voxel for Autonomous Drivingcited by 0
  12. 2025Text2Loc++: Generalizing 3D Point Cloud Localization from Natural Languagecited by 0
  13. 2025AVOID: The Adverse Visual Conditions Dataset with Obstacles for Driving Scene Understandingcited by 0