task_path stringlengths 3 199 ⌀ | dataset stringlengths 1 128 ⌀ | model_name stringlengths 1 223 ⌀ | paper_url stringlengths 21 601 ⌀ | metric_name stringlengths 1 50 ⌀ | metric_value stringlengths 1 9.22k ⌀ |
|---|---|---|---|---|---|
Autonomous Vehicles > Lane Detection | CurveLanes | CurveLane-S | https://arxiv.org/abs/2007.12147v1 | Precision | 93.58 |
Autonomous Vehicles > Lane Detection | CurveLanes | CurveLane-S | https://arxiv.org/abs/2007.12147v1 | Recall | 71.59 |
Autonomous Vehicles > Lane Detection | CurveLanes | CurveLane-S | https://arxiv.org/abs/2007.12147v1 | GFLOPs | 7.4 |
Autonomous Vehicles > Lane Detection | CurveLanes | PointLaneNet | https://arxiv.org/abs/2007.12147v1 | F1 score | 78.47 |
Autonomous Vehicles > Lane Detection | CurveLanes | PointLaneNet | https://arxiv.org/abs/2007.12147v1 | Precision | 86.33 |
Autonomous Vehicles > Lane Detection | CurveLanes | PointLaneNet | https://arxiv.org/abs/2007.12147v1 | Recall | 72.91 |
Autonomous Vehicles > Lane Detection | CurveLanes | PointLaneNet | https://arxiv.org/abs/2007.12147v1 | GFLOPs | 14.8 |
Autonomous Vehicles > Lane Detection | CurveLanes | SCNN | https://arxiv.org/abs/2007.12147v1 | F1 score | 65.02 |
Autonomous Vehicles > Lane Detection | CurveLanes | SCNN | https://arxiv.org/abs/2007.12147v1 | Precision | 76.13 |
Autonomous Vehicles > Lane Detection | CurveLanes | SCNN | https://arxiv.org/abs/2007.12147v1 | Recall | 56.74 |
Autonomous Vehicles > Lane Detection | CurveLanes | SCNN | https://arxiv.org/abs/2007.12147v1 | GFLOPs | 328.4 |
Autonomous Vehicles > Lane Detection | CurveLanes | Enet-SAD | https://arxiv.org/abs/2007.12147v1 | F1 score | 50.31 |
Autonomous Vehicles > Lane Detection | CurveLanes | Enet-SAD | https://arxiv.org/abs/2007.12147v1 | Precision | 63.6 |
Autonomous Vehicles > Lane Detection | CurveLanes | Enet-SAD | https://arxiv.org/abs/2007.12147v1 | Recall | 41.6 |
Autonomous Vehicles > Lane Detection | CurveLanes | Enet-SAD | https://arxiv.org/abs/2007.12147v1 | GFLOPs | 3.9 |
Autonomous Vehicles > Lane Detection | CurveLanes | CANet-L(ResNet101) | https://arxiv.org/abs/2304.11546v1 | Recall | 84.36 |
Autonomous Vehicles > Lane Detection | CurveLanes | CANet-L(ResNet101) | https://arxiv.org/abs/2304.11546v1 | GFLOPs | 45.7 |
Autonomous Vehicles > Lane Detection | Caltech Lanes Washington | VPGNet | http://arxiv.org/abs/1710.06288v1 | F1 | 0.869 |
Autonomous Vehicles > Lane Detection | Caltech Lanes Washington | Overfeat CNN detector + DBSCAN | http://arxiv.org/abs/1504.01716v3 | F1 | 0.861 |
Autonomous Vehicles > Lane Detection | K-Lane | LLDN-GFC | https://arxiv.org/abs/2110.11048v3 | F1 | 82.12 |
Autonomous Vehicles > Lane Detection | Caltech Lanes Cordova | VPGNet | http://arxiv.org/abs/1710.06288v1 | F1 | 0.884 |
Autonomous Vehicles > Lane Detection | Caltech Lanes Cordova | Overfeat CNN detector + DBSCAN | http://arxiv.org/abs/1504.01716v3 | F1 | 0.866 |
Autonomous Vehicles > Lane Detection | DET | LDNet | https://arxiv.org/abs/2009.08020v2 | event-based F1 score | 75.58 |
Autonomous Vehicles > Lane Detection | DET | LDNet | https://arxiv.org/abs/2009.08020v2 | Average IOU | 62.79 |
Autonomous Vehicles > Lane Detection | OpenLane-V2 val | TopoLogic | https://arxiv.org/abs/2405.14747v1 | mAP | 33.2 |
Autonomous Vehicles > Lane Detection | nuScenes | DSLP | https://arxiv.org/abs/2304.13242v2 | IoU | 0.453 |
Autonomous Vehicles > Lane Detection | nuScenes | DSLP | https://arxiv.org/abs/2304.13242v2 | F1 score | 0.853 |
Autonomous Vehicles > Lane Detection | nuScenes | LaneGraphNet | https://arxiv.org/abs/2105.00195v1 | IoU | 0.420 |
Autonomous Vehicles > Lane Detection | nuScenes | LaneGraphNet | https://arxiv.org/abs/2105.00195v1 | F1 score | 0.574 |
Autonomous Vehicles > Lane Detection | nuScenes | STSU | https://arxiv.org/abs/2110.01997v1 | IoU | 0.389 |
Autonomous Vehicles > Lane Detection | nuScenes | STSU | https://arxiv.org/abs/2110.01997v1 | F1 score | 0.560 |
Autonomous Vehicles > Lane Detection | BDD100K val | TwinLiteNetPlus-Large | https://arxiv.org/abs/2403.16958v1 | Accuracy (%) | 81.9 |
Autonomous Vehicles > Lane Detection | BDD100K val | TwinLiteNetPlus-Large | https://arxiv.org/abs/2403.16958v1 | Params (M) | 1.94 |
Autonomous Vehicles > Lane Detection | BDD100K val | TwinLiteNetPlus-Large | https://arxiv.org/abs/2403.16958v1 | IoU (%) | 34.2 |
Autonomous Vehicles > Lane Detection | BDD100K val | TwinLiteNetPlus-Medium | https://arxiv.org/abs/2403.16958v1 | Accuracy (%) | 79.1 |
Autonomous Vehicles > Lane Detection | BDD100K val | TwinLiteNetPlus-Medium | https://arxiv.org/abs/2403.16958v1 | Params (M) | 0.48 |
Autonomous Vehicles > Lane Detection | BDD100K val | TwinLiteNetPlus-Medium | https://arxiv.org/abs/2403.16958v1 | IoU (%) | 32.3 |
Autonomous Vehicles > Lane Detection | BDD100K val | HybridNets | https://arxiv.org/abs/2203.09035v1 | Accuracy (%) | 85.4 |
Autonomous Vehicles > Lane Detection | BDD100K val | HybridNets | https://arxiv.org/abs/2203.09035v1 | Params (M) | 12.8 |
Autonomous Vehicles > Lane Detection | BDD100K val | HybridNets | https://arxiv.org/abs/2203.09035v1 | IoU (%) | 31.6 |
Autonomous Vehicles > Lane Detection | BDD100K val | TwinLiteNet | https://arxiv.org/abs/2307.10705v5 | Accuracy (%) | 77.8 |
Autonomous Vehicles > Lane Detection | BDD100K val | TwinLiteNet | https://arxiv.org/abs/2307.10705v5 | Params (M) | 0.43 |
Autonomous Vehicles > Lane Detection | BDD100K val | TwinLiteNet | https://arxiv.org/abs/2307.10705v5 | IoU (%) | 31.08 |
Autonomous Vehicles > Lane Detection | BDD100K val | TriLiteNet-base | https://ieeexplore.ieee.org/document/10930421 | Accuracy (%) | 82.3 |
Autonomous Vehicles > Lane Detection | BDD100K val | TriLiteNet-base | https://ieeexplore.ieee.org/document/10930421 | Params (M) | 2.35 |
Autonomous Vehicles > Lane Detection | BDD100K val | TriLiteNet-base | https://ieeexplore.ieee.org/document/10930421 | IoU (%) | 29.8 |
Autonomous Vehicles > Lane Detection | BDD100K val | TwinLiteNetPlus-Small | https://arxiv.org/abs/2403.16958v1 | Accuracy (%) | 75.8 |
Autonomous Vehicles > Lane Detection | BDD100K val | TwinLiteNetPlus-Small | https://arxiv.org/abs/2403.16958v1 | Params (M) | 0.12 |
Autonomous Vehicles > Lane Detection | BDD100K val | TwinLiteNetPlus-Small | https://arxiv.org/abs/2403.16958v1 | IoU (%) | 29.3 |
Autonomous Vehicles > Lane Detection | BDD100K val | A-YOLOM(s) | https://arxiv.org/abs/2310.01641v4 | Accuracy (%) | 84.9 |
Autonomous Vehicles > Lane Detection | BDD100K val | A-YOLOM(s) | https://arxiv.org/abs/2310.01641v4 | IoU (%) | 28.8 |
Autonomous Vehicles > Lane Detection | BDD100K val | YOLOPv2 | https://arxiv.org/abs/2208.11434v1 | Accuracy (%) | 87.8 |
Autonomous Vehicles > Lane Detection | BDD100K val | YOLOPv2 | https://arxiv.org/abs/2208.11434v1 | Params (M) | 38.9 |
Autonomous Vehicles > Lane Detection | BDD100K val | YOLOPv2 | https://arxiv.org/abs/2208.11434v1 | IoU (%) | 27.25 |
Autonomous Vehicles > Lane Detection | BDD100K val | YOLOP | https://arxiv.org/abs/2108.11250v7 | Accuracy (%) | 70.5 |
Autonomous Vehicles > Lane Detection | BDD100K val | YOLOP | https://arxiv.org/abs/2108.11250v7 | Params (M) | 7.9 |
Autonomous Vehicles > Lane Detection | BDD100K val | YOLOP | https://arxiv.org/abs/2108.11250v7 | IoU (%) | 26.2 |
Autonomous Vehicles > Lane Detection | BDD100K val | TwinLiteNetPlus-Nano | https://arxiv.org/abs/2403.16958v1 | Accuracy (%) | 70.2 |
Autonomous Vehicles > Lane Detection | BDD100K val | TwinLiteNetPlus-Nano | https://arxiv.org/abs/2403.16958v1 | Params (M) | 0.03 |
Autonomous Vehicles > Lane Detection | BDD100K val | TwinLiteNetPlus-Nano | https://arxiv.org/abs/2403.16958v1 | IoU (%) | 23.3 |
Autonomous Vehicles > Lane Detection | BDD100K val | Enet-SAD | https://arxiv.org/abs/1908.00821v1 | Accuracy (%) | 36.6 |
Autonomous Vehicles > Lane Detection | BDD100K val | Enet-SAD | https://arxiv.org/abs/1908.00821v1 | IoU (%) | 16.02 |
Autonomous Vehicles > Lane Detection | CULane | DLNet | https://github.com/RDXiaoLu/DLNet.git | F1 score | 81.23 |
Autonomous Vehicles > Lane Detection | CULane | CLRerNet-DLA34 | https://arxiv.org/abs/2305.08366v1 | F1 score | 81.12 |
Autonomous Vehicles > Lane Detection | CULane | CLRerNet-Res101 | https://arxiv.org/abs/2305.08366v1 | F1 score | 80.91 |
Autonomous Vehicles > Lane Detection | CULane | CondLSTR(ResNet-101) | http://openaccess.thecvf.com//content/ICCV2023/html/Chen_Generating_Dynamic_Kernels_via_Transformers_for_Lane_Detection_ICCV_2023_paper.html | F1 score | 80.77 |
Autonomous Vehicles > Lane Detection | CULane | CLRerNet-Res34 | https://arxiv.org/abs/2305.08366v1 | F1 score | 80.76 |
Autonomous Vehicles > Lane Detection | CULane | CLRNetV2 (DLA34) | https://ieeexplore.ieee.org/abstract/document/10930685 | F1 score | 80.68 |
Autonomous Vehicles > Lane Detection | CULane | CLRNetV2 (DLA34) | https://ieeexplore.ieee.org/abstract/document/10930685 | mF1 | 57.27 |
Autonomous Vehicles > Lane Detection | CULane | CLRKDNet (DLA-34) | https://arxiv.org/abs/2405.12503v1 | F1 score | 80.68 |
Autonomous Vehicles > Lane Detection | CULane | CondLSTR(ResNet-34) | http://openaccess.thecvf.com//content/ICCV2023/html/Chen_Generating_Dynamic_Kernels_via_Transformers_for_Lane_Detection_ICCV_2023_paper.html | F1 score | 80.55 |
Autonomous Vehicles > Lane Detection | CULane | CLRNet(DLA-34) | https://arxiv.org/abs/2203.10350v1 | F1 score | 80.47 |
Autonomous Vehicles > Lane Detection | CULane | CLRNetV2 (ResNet101) | https://ieeexplore.ieee.org/abstract/document/10930685 | F1 score | 80.43 |
Autonomous Vehicles > Lane Detection | CULane | CondLSTR(ResNet-18) | http://openaccess.thecvf.com//content/ICCV2023/html/Chen_Generating_Dynamic_Kernels_via_Transformers_for_Lane_Detection_ICCV_2023_paper.html | F1 score | 80.36 |
Autonomous Vehicles > Lane Detection | CULane | FENetV2 | https://arxiv.org/abs/2312.17163v6 | F1 score | 80.19 |
Autonomous Vehicles > Lane Detection | CULane | FENetV2 | https://arxiv.org/abs/2312.17163v6 | mF1 | 56.17 |
Autonomous Vehicles > Lane Detection | CULane | FENetV1 | https://arxiv.org/abs/2312.17163v6 | F1 score | 80.15 |
Autonomous Vehicles > Lane Detection | CULane | FENetV1 | https://arxiv.org/abs/2312.17163v6 | mF1 | 56.27 |
Autonomous Vehicles > Lane Detection | CULane | CLRNet(ResNet-101) | https://arxiv.org/abs/2203.10350v1 | F1 score | 80.13 |
Autonomous Vehicles > Lane Detection | CULane | CLRmatchNet (Enhancing curved lane, Resnet-101) | https://arxiv.org/abs/2309.15204v2 | F1 score | 80.00 |
Autonomous Vehicles > Lane Detection | CULane | CLRNetV2 (ResNet34) | https://ieeexplore.ieee.org/abstract/document/10930685 | F1 score | 79.94 |
Autonomous Vehicles > Lane Detection | CULane | CANet-L(ResNet101) | https://arxiv.org/abs/2304.11546v1 | F1 score | 79.86 |
Autonomous Vehicles > Lane Detection | CULane | CLRNet(ResNet-34) | https://arxiv.org/abs/2203.10350v1 | F1 score | 79.73 |
Autonomous Vehicles > Lane Detection | CULane | CLRNetV2 (ResNet18) | https://ieeexplore.ieee.org/abstract/document/10930685 | F1 score | 79.68 |
Autonomous Vehicles > Lane Detection | CULane | CLRKDNet (ResNet-18) | https://arxiv.org/abs/2405.12503v1 | F1 score | 79.66 |
Autonomous Vehicles > Lane Detection | CULane | GANet(ResNet-101) | https://arxiv.org/abs/2204.07335v1 | F1 score | 79.63 |
Autonomous Vehicles > Lane Detection | CULane | CLRNet(ResNet-18) | https://arxiv.org/abs/2203.10350v1 | F1 score | 79.58 |
Autonomous Vehicles > Lane Detection | CULane | CondLaneNet-L(ResNet-101) | https://arxiv.org/abs/2105.05003v3 | F1 score | 79.48 |
Autonomous Vehicles > Lane Detection | CULane | GANet(ResNet-34) | https://arxiv.org/abs/2204.07335v1 | F1 score | 79.39 |
Autonomous Vehicles > Lane Detection | CULane | CLRNet - CLLD | https://arxiv.org/abs/2308.08242v4 | F1 score | 79.27 |
Autonomous Vehicles > Lane Detection | CULane | CANet-M | https://arxiv.org/abs/2304.11546v1 | F1 score | 79.16 |
Autonomous Vehicles > Lane Detection | CULane | FOLOLane(ERFNet) | https://arxiv.org/abs/2105.13680v1 | F1 score | 78.8 |
Autonomous Vehicles > Lane Detection | CULane | GANet(ResNet-18) | https://arxiv.org/abs/2204.07335v1 | F1 score | 78.79 |
Autonomous Vehicles > Lane Detection | CULane | CondLaneNet-M(ResNet-34) | https://arxiv.org/abs/2105.05003v3 | F1 score | 78.74 |
Autonomous Vehicles > Lane Detection | CULane | CLRNetV2 (ResNet18-lite) | https://ieeexplore.ieee.org/abstract/document/10930685 | F1 score | 78.66 |
Autonomous Vehicles > Lane Detection | CULane | CANet-S(ResNet18) | https://arxiv.org/abs/2304.11546v1 | F1 score | 78.46 |
Autonomous Vehicles > Lane Detection | CULane | CondLaneNet-S(ResNet-18) | https://arxiv.org/abs/2105.05003v3 | F1 score | 78.14 |
Autonomous Vehicles > Lane Detection | CULane | AtrousFormer(ResNet-34) | https://arxiv.org/abs/2203.04067v1 | F1 score | 78.08 |
Autonomous Vehicles > Lane Detection | CULane | O2SFormer(ResNet50) | https://arxiv.org/abs/2305.00675v4 | F1 score | 78.0 |
Autonomous Vehicles > Lane Detection | CULane | AtrousFormer(ResNet-18) | https://arxiv.org/abs/2203.04067v1 | F1 score | 77.63 |
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