mlsanityData to 14 Oct 2026

MFSeg: Efficient Multi-frame 3D Semantic Segmentation

arXiv 2505.04408 ↗First posted 7 May 2025cs.CVcited by 0

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Abstract (arXiv)

We propose MFSeg, an efficient multi-frame 3D semantic segmentation framework. By aggregating point cloud sequences at the feature level and regularizing the feature extraction and aggregation process, MFSeg reduces computational overhead while maintaining high accuracy. Moreover, by employing a lightweight MLP-based point decoder, our method eliminates the need to upsample redundant points from past frames. Experiments on the nuScenes and Waymo datasets show that MFSeg outperforms existing methods, demonstrating its effectiveness and efficiency.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 28 of its 33 references that are in the map. First posted on arXiv 7 May 2025.

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28 of 33 references.

References · 28

  1. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,248
  2. 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,523
  3. 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,401
  4. 2022FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awarenesscited by 3,673
  5. 2019Scalability in Perception for Autonomous Driving: Waymo Open Datasetcited by 2,451
  6. 2020Point Transformercited by 1,470
  7. 20194D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networkscited by 1,208
  8. 20173D Semantic Segmentation with Submanifold Sparse Convolutional Networkscited by 748
  9. 2023Point Transformer V3: Simpler, Faster, Strongercited by 589
  10. 2020Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentationcited by 389
  11. 2022Point Transformer V2: Grouped Vector Attention and Partition-based Poolingcited by 388
  12. 2019Point-Voxel CNN for Efficient 3D Deep Learningcited by 343
16 more
  1. 2020PolarNet: An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentationcited by 275
  2. 2017SqueezeSeg: Convolutional Neural Nets with Recurrent CRF for Real-Time Road-Object Segmentation from 3D LiDAR Point Cloudcited by 232
  3. 2018SqueezeSegV2: Improved Model Structure and Unsupervised Domain Adaptation for Road-Object Segmentation from a LiDAR Point Cloudcited by 228
  4. 2017Submanifold Sparse Convolutional Networkscited by 223
  5. 2021RPVNet: A Deep and Efficient Range-Point-Voxel Fusion Network for LiDAR Point Cloud Segmentationcited by 173
  6. 2020SqueezeSegV3: Spatially-Adaptive Convolution for Efficient Point-Cloud Segmentationcited by 170
  7. 20222DPASS: 2D Priors Assisted Semantic Segmentation on LiDAR Point Cloudscited by 158
  8. 2023Spherical Transformer for LiDAR-based 3D Recognitioncited by 125
  9. 2022Point-to-Voxel Knowledge Distillation for LiDAR Semantic Segmentationcited by 119
  10. 20213D-MAN: 3D Multi-frame Attention Network for Object Detectioncited by 73
  11. 2023MSeg3D: Multi-modal 3D Semantic Segmentation for Autonomous Drivingcited by 68
  12. 2022MPPNet: Multi-Frame Feature Intertwining with Proxy Points for 3D Temporal Object Detectioncited by 65
  13. 2023UniSeg: A Unified Multi-Modal LiDAR Segmentation Network and the OpenPCSeg Codebasecited by 57
  14. 2022Meta-RangeSeg: LiDAR Sequence Semantic Segmentation Using Multiple Feature Aggregationcited by 23
  15. 2022Abstract Flow for Temporal Semantic Segmentation on the Permutohedral Latticecited by 9
  16. 2024SOAP: Cross-sensor Domain Adaptation for 3D Object Detection Using Stationary Object Aggregation Pseudo-labellingcited by 8

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