mlsanityData to 14 Oct 2026

Hidden Gems: 4D Radar Scene Flow Learning Using Cross-Modal Supervision

arXiv 2303.00462 ↗First posted 1 Mar 2023cs.CV cs.AI cs.LGcited by 36

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Abstract (arXiv)

This work proposes a novel approach to 4D radar-based scene flow estimation via cross-modal learning. Our approach is motivated by the co-located sensing redundancy in modern autonomous vehicles. Such redundancy implicitly provides various forms of supervision cues to the radar scene flow estimation. Specifically, we introduce a multi-task model architecture for the identified cross-modal learning problem and propose loss functions to opportunistically engage scene flow estimation using multiple cross-modal constraints for effective model training. Extensive experiments show the state-of-the-art performance of our method and demonstrate the effectiveness of cross-modal supervised learning to infer more accurate 4D radar scene flow. We also show its usefulness to two subtasks - motion segmentation and ego-motion estimation. Our source code will be available on https://github.com/Toytiny/CMFlow.

Key facts. Cited by 36 papers in the map (data through 14 Oct 2026). Builds on 39 of its 67 references that are in the map. First posted on arXiv 1 Mar 2023.

Builds on

39 of 67 references.

References · 39

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27 more
  1. 2018GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Posecited by 342
  2. 2018FlowNet3D: Learning Scene Flow in 3D Point Cloudscited by 242
  3. 2018SPLATNet: Sparse Lattice Networks for Point Cloud Processingcited by 158
  4. 2018DF-Net: Unsupervised Joint Learning of Depth and Flow using Cross-Task Consistencycited by 148
  5. 2020FLOT: Scene Flow on Point Clouds Guided by Optimal Transportcited by 129
  6. 2020GNN3DMOT: Graph Neural Network for 3D Multi-Object Tracking with Multi-Feature Learningcited by 113
  7. 2019HPLFlowNet: Hierarchical Permutohedral Lattice FlowNet for Scene Flow Estimation on Large-scale Point Cloudscited by 109
  8. 2020Lidar for Autonomous Driving: The principles, challenges, and trends for automotive lidar and perception systemscited by 100
  9. 2019Just Go with the Flow: Self-Supervised Scene Flow Estimationcited by 98
  10. 2021Neural Scene Flow Priorcited by 91
  11. 2020PV-RAFT: Point-Voxel Correlation Fields for Scene Flow Estimation of Point Cloudscited by 74
  12. 2020FlowStep3D: Model Unrolling for Self-Supervised Scene Flow Estimationcited by 71
  13. 2018Occlusions, Motion and Depth Boundaries with a Generic Network for Disparity, Optical Flow or Scene Flow Estimationcited by 69
  14. 2020Self-Supervised Monocular Scene Flow Estimationcited by 64
  15. 2021Weakly Supervised Learning of Rigid 3D Scene Flowcited by 60
  16. 2019FlowNet3D++: Geometric Losses For Deep Scene Flow Estimationcited by 55
  17. 2021Scalable Scene Flow from Point Clouds in the Real Worldcited by 50
  18. 2020Scene Flow from Point Clouds with or without Learningcited by 44
  19. 2020Self-Supervised Learning of Non-Rigid Residual Flow and Ego-Motioncited by 41
  20. 2021Self-Point-Flow: Self-Supervised Scene Flow Estimation from Point Clouds with Optimal Transport and Random Walkcited by 39
  21. 2018Learning Rigidity in Dynamic Scenes with a Moving Camera for 3D Motion Field Estimationcited by 38
  22. 2019SENSE: a Shared Encoder Network for Scene-flow Estimationcited by 38
  23. 2022Bi-PointFlowNet: Bidirectional Learning for Point Cloud Based Scene Flow Estimationcited by 38
  24. 2021HCRF-Flow: Scene Flow from Point Clouds with Continuous High-order CRFs and Position-aware Flow Embeddingcited by 36
  25. 2022What Matters for 3D Scene Flow Networkcited by 31
  26. 2021FESTA: Flow Estimation via Spatial-Temporal Attention for Scene Point Cloudscited by 30
  27. 2022Self-Supervised Scene Flow Estimation with 4-D Automotive Radarcited by 29

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 8; 2024: 11; 2025: 12; 2026: 5.

36 papers.

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  1. 2023SMURF: Spatial Multi-Representation Fusion for 3D Object Detection with 4D Imaging Radarcited by 49
  2. 2024Unleashing HyDRa: Hybrid Fusion, Depth Consistency and Radar for Unified 3D Perceptioncited by 35
  3. 2024RadarOcc: Robust 3D Occupancy Prediction with 4D Imaging Radarcited by 33
  4. 2023Exploring Radar Data Representations in Autonomous Driving: A Comprehensive Reviewcited by 22
  5. 2025Doracamom: Joint 3D Detection and Occupancy Prediction with Multi-view 4D Radars and Cameras for Omnidirectional Perceptioncited by 22
  6. 2023RaTrack: Moving Object Detection and Tracking with 4D Radar Point Cloudcited by 21
  7. 2023milliFlow: Scene Flow Estimation on mmWave Radar Point Cloud for Human Motion Sensingcited by 20
  8. 2024DART: Implicit Doppler Tomography for Radar Novel View Synthesiscited by 19
  9. 2024Radar Fields: Frequency-Space Neural Scene Representations for FMCW Radarcited by 18
  10. 2024Towards Dense and Accurate Radar Perception Via Efficient Cross-Modal Diffusion Modelcited by 17
  11. 2024Bring Event into RGB and LiDAR: Hierarchical Visual-Motion Fusion for Scene Flowcited by 15
  12. 20234DRVO-Net: Deep 4D Radar-Visual Odometry Using Multi-Modal and Multi-Scale Adaptive Fusioncited by 11
24 more
  1. 2023Radars for Autonomous Driving: A Review of Deep Learning Methods and Challengescited by 10
  2. 2023Radar Instance Transformer: Reliable Moving Instance Segmentation in Sparse Radar Point Cloudscited by 9
  3. 2023Bootstrapping Autonomous Driving Radars with Self-Supervised Learningcited by 9
  4. 2024Radar and Camera Fusion for Object Detection and Tracking: A Comprehensive Surveycited by 9
  5. 2025TacoDepth: Towards Efficient Radar-Camera Depth Estimation with One-stage Fusioncited by 9
  6. 2025M4Human: A Large-Scale Multimodal mmWave Radar Benchmark for Human Mesh Reconstructioncited by 7
  7. 2024Self-Supervised Bird's Eye View Motion Prediction with Cross-Modality Signalscited by 5
  8. 2024SIRA: Scalable Inter-frame Relation and Association for Radar Perceptioncited by 4
  9. 2025DoGFlow: Self-Supervised LiDAR Scene Flow via Cross-Modal Doppler Guidancecited by 4
  10. 2024Instantaneous Perception of Moving Objects in 3Dcited by 3
  11. 2024LEROjD: Lidar Extended Radar-Only Object Detectioncited by 3
  12. 2025TARS: Traffic-Aware Radar Scene Flow Estimationcited by 3
  13. 2025RaLiFlow: Scene Flow Estimation with 4D Radar and LiDAR Point Cloudscited by 3
  14. 2026HyperDet: 3D Object Detection with Hyper 4D Radar Point Cloudscited by 3
  15. 2025RadarMP: Motion Perception for 4D mmWave Radar in Autonomous Drivingcited by 2
  16. 2025RISE: Single Static Radar-based Indoor Scene Understandingcited by 2
  17. 2025RLM: A Vision-Language Model Approach for Radar Scene Understandingcited by 2
  18. 2025RadarGen: Automotive Radar Point Cloud Generation from Camerascited by 2
  19. 2026R3D: Regional-guided Residual Radar Diffusioncited by 2
  20. 2025DNOI-4DRO: Deep 4D Radar Odometry with Differentiable Neural-Optimization Iterationscited by 1
  21. 2025VISC: mmWave Radar Scene Flow Estimation using Pervasive Visual-Inertial Supervisioncited by 0
  22. 2026Weakly Supervised Cross-Modal Learning for 4D Radar Scene Flow Estimationcited by 0
  23. 20264D Radar Perception Algorithms for Autonomous Driving: A Reviewcited by 0
  24. 2026DiFF: Doppler-informed Flow Matching for Human Motion Flowcited by 0