mlsanityData to 7 Oct 2026

DetFlowTrack: 3D Multi-object Tracking based on Simultaneous Optimization of Object Detection and Scene Flow Estimation

arXiv 2203.02157 ↗First posted 4 Mar 2022cs.CV cs.ROcited by 2

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Abstract (arXiv)

3D Multi-Object Tracking (MOT) is an important part of the unmanned vehicle perception module. Most methods optimize object detection and data association independently. These methods make the network structure complicated and limit the improvement of MOT accuracy. we proposed a 3D MOT framework based on simultaneous optimization of object detection and scene flow estimation. In the framework, a detection-guidance scene flow module is proposed to relieve the problem of incorrect inter-frame assocation. For more accurate scene flow label especially in the case of motion with rotation, a box-transformation-based scene flow ground truth calculation method is proposed. Experimental results on the KITTI MOT dataset show competitive results over the state-of-the-arts and the robustness under extreme motion with rotation.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 15 of its 18 references that are in the map. First posted on arXiv 4 Mar 2022.

Builds on

15 of 18 references.

References · 15

  1. 2015FlowNet: Learning Optical Flow with Convolutional Networkscited by 1,054
  2. 2017PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volumecited by 966
  3. 2019PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detectioncited by 890
  4. 2018PointConv: Deep Convolutional Networks on 3D Point Cloudscited by 656
  5. 2020HOTA: A Higher Order Metric for Evaluating Multi-Object Trackingcited by 546
  6. 2018FlowNet3D: Learning Scene Flow in 3D Point Cloudscited by 241
  7. 2017Super-Convergence: Very Fast Training of Neural Networks Using Large Learning Ratescited by 196
  8. 2020GNN3DMOT: Graph Neural Network for 3D Multi-Object Tracking with Multi-Feature Learningcited by 113
  9. 2020Probabilistic 3D Multi-Object Tracking for Autonomous Drivingcited by 64
  10. 2020JRMOT: A Real-Time 3D Multi-Object Tracker and a New Large-Scale Datasetcited by 39
  11. 2019PointPWC-Net: A Coarse-to-Fine Network for Supervised and Self-Supervised Scene Flow Estimation on 3D Point Cloudscited by 38
  12. 2019Complexer-YOLO: Real-Time 3D Object Detection and Tracking on Semantic Point Cloudscited by 35
3 more
  1. 2020PointTrackNet: An End-to-End Network For 3-D Object Detection and Tracking From Point Cloudscited by 20
  2. 2020Multiple Object Tracking by Flowing and Fusingcited by 17
  3. 2020FlowMOT: 3D Multi-Object Tracking by Scene Flow Associationcited by 10

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Cited by year

Citing papers per year: 2023: 1; 2024: 1.

2 papers.

  1. 2024DVN-SLAM: Dynamic Visual Neural SLAM Based on Local-Global Encodingcited by 6
  2. 20233D Multiple Object Tracking on Autonomous Driving: A Literature Reviewcited by 4