TasksSotADatasetsPapersMethodsSubmitAbout
Papers With Code 2

A community resource for machine learning research: papers, code, benchmarks, and state-of-the-art results.

Explore

Notable BenchmarksAll SotADatasetsPapersMethods

Community

Submit ResultsAbout

Data sourced from the PWC Archive (CC-BY-SA 4.0). Built by the community, for the community.

Models/BEV-LaneDet

BEV-LaneDet

Reported on 26 benchmarks across 2 tasks · 1 paper · 16 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Robots13 results

  • Autonomous VehiclesonApollo Synthetic 3D Lane
    F1· 2022-10-12
    96.9
    best: 97.4 (LaneCPP)
    SOTA
    BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselinearXiv:2210.06006
  • Autonomous VehiclesonApollo Synthetic 3D Lane
    X error far· 2022-10-12
    0.242
    SOTA
    BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselinearXiv:2210.06006
  • Autonomous VehiclesonApollo Synthetic 3D Lane
    X error near· 2022-10-12
    0.016
    SOTA
    BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselinearXiv:2210.06006
  • Autonomous VehiclesonOpenLane
    Curve· 2022-10-12
    63.1
    best: 72.7 (GLane3D(Swin-B))
    SOTA
    BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselinearXiv:2210.06006
  • Autonomous VehiclesonOpenLane
    FPS (pytorch)· 2022-10-12
    102
    SOTA
    BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselinearXiv:2210.06006
  • Autonomous VehiclesonOpenLane
    Intersection· 2022-10-12
    50.3
    best: 57.9 (GLane3D(Swin-B))
    SOTA
    BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselinearXiv:2210.06006
  • Autonomous VehiclesonOpenLane
    Merge & Split· 2022-10-12
    53.7
    best: 67.7 (GLane3D(Swin-B))
    SOTA
    BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselinearXiv:2210.06006
  • Autonomous VehiclesonOpenLane
    Night· 2022-10-12
    53.4
    best: 62 (GLane3D(Swin-B))
    SOTA
    BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselinearXiv:2210.06006
  • Autonomous VehiclesonApollo Synthetic 3D Lane
    Z error far· 2022-10-12
    0.216
    best: 0.202 (3D-LaneNet)
    BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselinearXiv:2210.06006
  • Autonomous VehiclesonApollo Synthetic 3D Lane
    Z error near· 2022-10-12
    0.02
    best: 0.008 (Reconstruct from Top View)
    BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselinearXiv:2210.06006
  • Autonomous VehiclesonOpenLane
    Extreme Weather· 2022-10-12
    53.4
    best: 64 (PVALane (Swin-B))
    BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselinearXiv:2210.06006
  • Autonomous VehiclesonOpenLane
    F1 (all)· 2022-10-12
    58.4
    best: 66 (GLane3D(Swin-B))
    BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselinearXiv:2210.06006
  • Autonomous VehiclesonOpenLane
    Up & Down· 2022-10-12
    48.7
    best: 61.7 (GLane3D(Swin-B))
    BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselinearXiv:2210.06006

Computer Vision13 results

  • Lane DetectiononApollo Synthetic 3D Lane
    F1· 2022-10-12
    96.9
    best: 97.4 (LaneCPP)
    SOTA
    BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselinearXiv:2210.06006
  • Lane DetectiononApollo Synthetic 3D Lane
    X error far· 2022-10-12
    0.242
    SOTA
    BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselinearXiv:2210.06006
  • Lane DetectiononApollo Synthetic 3D Lane
    X error near· 2022-10-12
    0.016
    SOTA
    BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselinearXiv:2210.06006
  • Lane DetectiononOpenLane
    Curve· 2022-10-12
    63.1
    best: 72.7 (GLane3D(Swin-B))
    SOTA
    BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselinearXiv:2210.06006
  • Lane DetectiononOpenLane
    FPS (pytorch)· 2022-10-12
    102
    SOTA
    BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselinearXiv:2210.06006
  • Lane DetectiononOpenLane
    Intersection· 2022-10-12
    50.3
    best: 57.9 (GLane3D(Swin-B))
    SOTA
    BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselinearXiv:2210.06006
  • Lane DetectiononOpenLane
    Merge & Split· 2022-10-12
    53.7
    best: 67.7 (GLane3D(Swin-B))
    SOTA
    BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselinearXiv:2210.06006
  • Lane DetectiononOpenLane
    Night· 2022-10-12
    53.4
    best: 62 (GLane3D(Swin-B))
    SOTA
    BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselinearXiv:2210.06006
  • Lane DetectiononApollo Synthetic 3D Lane
    Z error far· 2022-10-12
    0.216
    best: 0.202 (3D-LaneNet)
    BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselinearXiv:2210.06006
  • Lane DetectiononApollo Synthetic 3D Lane
    Z error near· 2022-10-12
    0.02
    best: 0.008 (Reconstruct from Top View)
    BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselinearXiv:2210.06006
  • Lane DetectiononOpenLane
    Extreme Weather· 2022-10-12
    53.4
    best: 64 (PVALane (Swin-B))
    BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselinearXiv:2210.06006
  • Lane DetectiononOpenLane
    F1 (all)· 2022-10-12
    58.4
    best: 66 (GLane3D(Swin-B))
    BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselinearXiv:2210.06006
  • Lane DetectiononOpenLane
    Up & Down· 2022-10-12
    48.7
    best: 61.7 (GLane3D(Swin-B))
    BEV-LaneDet: a Simple and Effective 3D Lane Detection BaselinearXiv:2210.06006