mlsanityData to 7 Oct 2026

InLUT3D: Challenging real indoor dataset for point cloud analysis

arXiv 2408.03338 ↗First posted 22 Jul 2024cs.CVcited by 1

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Abstract (arXiv)

In this paper, we introduce the InLUT3D point cloud dataset, a comprehensive resource designed to advance the field of scene understanding in indoor environments. The dataset covers diverse spaces within the W7 faculty buildings of Lodz University of Technology, characterised by high-resolution laser-based point clouds and manual labelling. Alongside the dataset, we propose metrics and benchmarking guidelines essential for ensuring trustworthy and reproducible results in algorithm evaluation. We anticipate that the introduction of the InLUT3D dataset and its associated benchmarks will catalyse future advancements in 3D scene understanding, facilitating methodological rigour and inspiring new approaches in the field.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 16 of its 23 references that are in the map. First posted on arXiv 22 Jul 2024.

Builds on

16 of 23 references.

References · 16

  1. 2018Dynamic Graph CNN for Learning on Point Cloudscited by 2,220
  2. 2018PointPillars: Fast Encoders for Object Detection from Point Cloudscited by 1,707
  3. 2023Point Transformer V3: Simpler, Faster, Strongercited by 579
  4. 2015Multi-view Convolutional Neural Networks for 3D Shape Recognitioncited by 564
  5. 2017Joint 2D-3D-Semantic Data for Indoor Scene Understandingcited by 404
  6. 2022Mask3D: Mask Transformer for 3D Semantic Instance Segmentationcited by 299
  7. 2017Semantic3D.net: A new Large-scale Point Cloud Classification Benchmarkcited by 158
  8. 2016Vehicle Detection from 3D Lidar Using Fully Convolutional Networkcited by 105
  9. 2023OctFormer: Octree-based Transformers for 3D Point Cloudscited by 105
  10. 2023Real3D-AD: A Dataset of Point Cloud Anomaly Detectioncited by 87
  11. 2023PonderV2: Pave the Way for 3D Foundation Model with A Universal Pre-training Paradigmcited by 56
  12. 2021Perceptual Quality Assessment of Colored 3D Point Cloudscited by 49
4 more
  1. 2023V-DETR: DETR with Vertex Relative Position Encoding for 3D Object Detectioncited by 34
  2. 2023TR3D: Towards Real-Time Indoor 3D Object Detectioncited by 32
  3. 2023Building3D: An Urban-Scale Dataset and Benchmarks for Learning Roof Structures from Point Cloudscited by 24
  4. 2023Tinto: Multisensor Benchmark for 3D Hyperspectral Point Cloud Segmentation in the Geosciencescited by 4

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Citing papers per year: 2025: 1.

1 paper.

  1. 2025Through the Perspective of LiDAR: A Feature-Enriched and Uncertainty-Aware Annotation Pipeline for Terrestrial Point Cloud Segmentationcited by 0