mlsanityData to 7 Oct 2026

FuseSeg: LiDAR Point Cloud Segmentation Fusing Multi-Modal Data

arXiv 1912.08487 ↗First posted 18 Dec 2019cs.CV cs.ROcited by 33

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Abstract (arXiv)

We introduce a simple yet effective fusion method of LiDAR and RGB data to segment LiDAR point clouds. Utilizing the dense native range representation of a LiDAR sensor and the setup calibration, we establish point correspondences between the two input modalities. Subsequently, we are able to warp and fuse the features from one domain into the other. Therefore, we can jointly exploit information from both data sources within one single network. To show the merit of our method, we extend SqueezeSeg, a point cloud segmentation network, with an RGB feature branch and fuse it into the original structure. Our extension called FuseSeg leads to an improvement of up to 18% IoU on the KITTI benchmark. In addition to the improved accuracy, we also achieve real-time performance at 50 fps, five times as fast as the KITTI LiDAR data recording speed.

Key facts. Cited by 33 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Dec 2019.

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Citing papers per year: 2021: 3; 2022: 8; 2023: 9; 2024: 9; 2025: 3; 2026: 1.

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  1. 20222DPASS: 2D Priors Assisted Semantic Segmentation on LiDAR Point Cloudscited by 157
  2. 2023MSeg3D: Multi-modal 3D Semantic Segmentation for Autonomous Drivingcited by 68
  3. 2024OmniSat: Self-Supervised Modality Fusion for Earth Observationcited by 63
  4. 2023Grounding 3D Object Affordance from 2D Interactions in Imagescited by 62
  5. 2021EPMF: Efficient Perception-aware Multi-sensor Fusion for 3D Semantic Segmentationcited by 59
  6. 2023UniSeg: A Unified Multi-Modal LiDAR Segmentation Network and the OpenPCSeg Codebasecited by 57
  7. 2022Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentationcited by 47
  8. 2022Homogeneous Multi-modal Feature Fusion and Interaction for 3D Object Detectioncited by 26
  9. 2022Let Images Give You More:Point Cloud Cross-Modal Training for Shape Analysiscited by 24
  10. 2024Learning 2D Invariant Affordance Knowledge for 3D Affordance Groundingcited by 21
  11. 2023Learning to Adapt SAM for Segmenting Cross-domain Point Cloudscited by 20
  12. 2024Multimodality Helps Few-shot 3D Point Cloud Semantic Segmentationcited by 20
21 more
  1. 2024No Time to Train: Empowering Non-Parametric Networks for Few-shot 3D Scene Segmentationcited by 18
  2. 2023WildScenes: A Benchmark for 2D and 3D Semantic Segmentation in Large-scale Natural Environmentscited by 16
  3. 2022Image Understands Point Cloud: Weakly Supervised 3D Semantic Segmentation via Association Learningcited by 15
  4. 2023Exploiting the Complementarity of 2D and 3D Networks to Address Domain-Shift in 3D Semantic Segmentationcited by 14
  5. 2024TASeg: Temporal Aggregation Network for LiDAR Semantic Segmentationcited by 13
  6. 2023Recent Advances in Multi-modal 3D Intelligence: A Comprehensive Survey and Evaluationcited by 12
  7. 2025How Do Images Align and Complement LiDAR? Towards a Harmonized Multi-modal 3D Panoptic Segmentationcited by 7
  8. 2023Continual Road-Scene Semantic Segmentation via Feature-Aligned Symmetric Multi-Modal Networkcited by 6
  9. 2024ZOPP: A Framework of Zero-shot Offboard Panoptic Perception for Autonomous Drivingcited by 6
  10. 2025Veila: Panoramic LiDAR Generation from a Monocular RGB Imagecited by 5
  11. 2024Fusion-then-Distillation: Toward Cross-modal Positive Distillation for Domain Adaptive 3D Semantic Segmentationcited by 4
  12. 2022Learning Scene Flow in 3D Point Clouds with Noisy Pseudo Labelscited by 3
  13. 2022DepthFormer: Multimodal Positional Encodings and Cross-Input Attention for Transformer-Based Segmentation Networkscited by 3
  14. 2022Normal Transformer: Extracting Surface Geometry from LiDAR Points Enhanced by Visual Semanticscited by 2
  15. 2023Revisiting Multi-modal 3D Semantic Segmentation in Real-world Autonomous Drivingcited by 2
  16. 2024Sparse Point Clouds Assisted Learned Image Compressioncited by 1
  17. 2021Evaluation of Multimodal Semantic Segmentation using RGB-D Datacited by 0
  18. 2021FPPN: Future Pseudo-LiDAR Frame Prediction for Autonomous Drivingcited by 0
  19. 2024Towards Semi-supervised Dual-modal Semantic Segmentationcited by 0
  20. 2025Domain Adaptation-Based Crossmodal Knowledge Distillation for 3D Semantic Segmentationcited by 0
  21. 2026Contextual Range-View Projection for 3D LiDAR Point Cloudscited by 0