mlsanityData to 7 Oct 2026

Online Segmentation of LiDAR Sequences: Dataset and Algorithm

arXiv 2206.08194 ↗First posted 16 Jun 2022cs.CVcited by 14

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Abstract (arXiv)

Roof-mounted spinning LiDAR sensors are widely used by autonomous vehicles. However, most semantic datasets and algorithms used for LiDAR sequence segmentation operate on 360^circ frames, causing an acquisition latency incompatible with real-time applications. To address this issue, we first introduce HelixNet, a 10 billion point dataset with fine-grained labels, timestamps, and sensor rotation information necessary to accurately assess the real-time readiness of segmentation algorithms. Second, we propose Helix4D, a compact and efficient spatio-temporal transformer architecture specifically designed for rotating LiDAR sequences. Helix4D operates on acquisition slices corresponding to a fraction of a full sensor rotation, significantly reducing the total latency. Helix4D reaches accuracy on par with the best segmentation algorithms on HelixNet and SemanticKITTI with a reduction of over 5× in terms of latency and 50× in model size. The code and data are available at: https://romainloiseau.fr/helixnet

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). Builds on 41 of its 57 references that are in the map. First posted on arXiv 16 Jun 2022.

Builds on

41 of 57 references.

References · 41

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 5; 2024: 4; 2025: 3; 2026: 1.

14 papers.

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  1. 2023Efficient 3D Semantic Segmentation with Superpoint Transformercited by 56
  2. 2022Domain generalization of 3D semantic segmentation in autonomous drivingcited by 25
  3. 2024Scalable 3D Panoptic Segmentation As Superpoint Graph Clusteringcited by 14
  4. 2023Navya3DSeg -- Navya 3D Semantic Segmentation Dataset & split generation for autonomous vehiclescited by 9
  5. 2024Lidar Panoptic Segmentation in an Open Worldcited by 7
  6. 2023ParisLuco3D: A high-quality target dataset for domain generalization of LiDAR perceptioncited by 5
  7. 2024ZAHA: Introducing the Level of Facade Generalization and the Large-Scale Point Cloud Facade Semantic Segmentation Benchmark Datasetcited by 3
  8. 2025FLARES: Fast and Accurate LiDAR Multi-Range Semantic Segmentationcited by 3
  9. 2025TrueCity: Real and Simulated Urban Data for Cross-Domain 3D Scene Understandingcited by 2
  10. 2023Semantic Segmentation on 3D Point Clouds with High Density Variationscited by 1
  11. 2025EZ-SP: Fast and Lightweight Superpoint-Based 3D Segmentationcited by 1
  12. 2026UnderOneFacade: Worldwide Facade Semantic Segmentation Benchmark Datasetcited by 1
2 more
  1. 2023Low Latency Instance Segmentation by Continuous Clustering for LiDAR Sensorscited by 0
  2. 2024ARCH2S: Dataset, Benchmark and Challenges for Learning Exterior Architectural Structures from Point Cloudscited by 0