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 > Pedestrian Detection | CityPersons | Beta R-CNN | https://arxiv.org/abs/2210.12758v1 | Heavy MR^-2 | 47.1 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | Beta R-CNN | https://arxiv.org/abs/2210.12758v1 | Partial MR^-2 | 10.3 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | Beta R-CNN | https://arxiv.org/abs/2210.12758v1 | Bare MR^-2 | 6.4 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | FRCNN+FPN-Res50+refined feature map+Crowdhuman | http://arxiv.org/abs/1805.00123v1 | Reasonable MR^-2 | 10.67 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | NOH-NMS | https://arxiv.org/abs/2007.13376v1 | Reasonable MR^-2 | 10.8 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | NOH-NMS | https://arxiv.org/abs/2007.13376v1 | Heavy MR^-2 | 53.0 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | NOH-NMS | https://arxiv.org/abs/2007.13376v1 | Partial MR^-2 | 11.2 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | NOH-NMS | https://arxiv.org/abs/2007.13376v1 | Bare MR^-2 | 6.6 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | CSP (with offset) + ResNet-50 | https://arxiv.org/abs/1904.02948v4 | Reasonable MR^-2 | 11.0 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | CSP (with offset) + ResNet-50 | https://arxiv.org/abs/1904.02948v4 | Heavy MR^-2 | 49.3 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | CSP (with offset) + ResNet-50 | https://arxiv.org/abs/1904.02948v4 | Partial MR^-2 | 10.4 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | CSP (with offset) + ResNet-50 | https://arxiv.org/abs/1904.02948v4 | Bare MR^-2 | 7.3 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | CSP (with offset) + ResNet-50 | https://arxiv.org/abs/1904.02948v4 | Small MR^-2 | 16.0 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | CSP (with offset) + ResNet-50 | https://arxiv.org/abs/1904.02948v4 | Medium MR^-2 | 3.7 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | CSP (with offset) + ResNet-50 | https://arxiv.org/abs/1904.02948v4 | Large MR^-2 | 6.5 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | CSP (with offset) + ResNet-50 | https://arxiv.org/abs/1904.02948v4 | Test Time | 0.33s/img |
Autonomous Vehicles > Pedestrian Detection | CityPersons | ALFNet | http://openaccess.thecvf.com/content_ECCV_2018/html/Wei_Liu_Learning_Efficient_Single-stage_ECCV_2018_paper.html | Reasonable MR^-2 | 12.0 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | ALFNet | http://openaccess.thecvf.com/content_ECCV_2018/html/Wei_Liu_Learning_Efficient_Single-stage_ECCV_2018_paper.html | Heavy MR^-2 | 51.9 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | ALFNet | http://openaccess.thecvf.com/content_ECCV_2018/html/Wei_Liu_Learning_Efficient_Single-stage_ECCV_2018_paper.html | Partial MR^-2 | 11.4 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | ALFNet | http://openaccess.thecvf.com/content_ECCV_2018/html/Wei_Liu_Learning_Efficient_Single-stage_ECCV_2018_paper.html | Bare MR^-2 | 8.4 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | ALFNet | http://openaccess.thecvf.com/content_ECCV_2018/html/Wei_Liu_Learning_Efficient_Single-stage_ECCV_2018_paper.html | Small MR^-2 | 19.0 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | ALFNet | http://openaccess.thecvf.com/content_ECCV_2018/html/Wei_Liu_Learning_Efficient_Single-stage_ECCV_2018_paper.html | Medium MR^-2 | 5.7 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | ALFNet | http://openaccess.thecvf.com/content_ECCV_2018/html/Wei_Liu_Learning_Efficient_Single-stage_ECCV_2018_paper.html | Large MR^-2 | 6.6 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | ALFNet | http://openaccess.thecvf.com/content_ECCV_2018/html/Wei_Liu_Learning_Efficient_Single-stage_ECCV_2018_paper.html | Test Time | 0.27 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | OR-CNN | http://arxiv.org/abs/1807.08407v1 | Reasonable MR^-2 | 12.8 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | OR-CNN | http://arxiv.org/abs/1807.08407v1 | Heavy MR^-2 | 55.7 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | OR-CNN | http://arxiv.org/abs/1807.08407v1 | Partial MR^-2 | 15.3 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | OR-CNN | http://arxiv.org/abs/1807.08407v1 | Bare MR^-2 | 6.7 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | RepLoss | http://arxiv.org/abs/1711.07752v2 | Reasonable MR^-2 | 13.2 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | RepLoss | http://arxiv.org/abs/1711.07752v2 | Heavy MR^-2 | 56.9 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | RepLoss | http://arxiv.org/abs/1711.07752v2 | Partial MR^-2 | 16.8 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | RepLoss | http://arxiv.org/abs/1711.07752v2 | Bare MR^-2 | 7.6 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | TLL+MRF | http://arxiv.org/abs/1807.01438v1 | Reasonable MR^-2 | 14.4 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | TLL+MRF | http://arxiv.org/abs/1807.01438v1 | Heavy MR^-2 | 52.0 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | TLL+MRF | http://arxiv.org/abs/1807.01438v1 | Partial MR^-2 | 15.9 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | TLL+MRF | http://arxiv.org/abs/1807.01438v1 | Bare MR^-2 | 9.2 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | FRCNN+Seg | http://arxiv.org/abs/1702.05693v1 | Reasonable MR^-2 | 14.8 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | FRCNN+Seg | http://arxiv.org/abs/1702.05693v1 | Small MR^-2 | 22.6 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | FRCNN+Seg | http://arxiv.org/abs/1702.05693v1 | Medium MR^-2 | 6.7 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | FRCNN+Seg | http://arxiv.org/abs/1702.05693v1 | Large MR^-2 | 8.0 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | FRCNN | http://arxiv.org/abs/1702.05693v1 | Reasonable MR^-2 | 15.4 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | FRCNN | http://arxiv.org/abs/1702.05693v1 | Small MR^-2 | 25.6 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | FRCNN | http://arxiv.org/abs/1702.05693v1 | Medium MR^-2 | 7.2 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | FRCNN | http://arxiv.org/abs/1702.05693v1 | Large MR^-2 | 7.9 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | TLL | http://arxiv.org/abs/1807.01438v1 | Reasonable MR^-2 | 15.5 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | TLL | http://arxiv.org/abs/1807.01438v1 | Heavy MR^-2 | 53.6 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | TLL | http://arxiv.org/abs/1807.01438v1 | Partial MR^-2 | 17.2 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | TLL | http://arxiv.org/abs/1807.01438v1 | Bare MR^-2 | 10.0 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | ACSP + EuroCity Persons | https://arxiv.org/abs/2002.09053v2 | Heavy MR^-2 | 42.5 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | ACSP + EuroCity Persons | https://arxiv.org/abs/2002.09053v2 | Partial MR^-2 | 6.9 |
Autonomous Vehicles > Pedestrian Detection | CityPersons | ACSP + EuroCity Persons | https://arxiv.org/abs/2002.09053v2 | Bare MR^-2 | 4.9 |
Autonomous Vehicles > Pedestrian Detection > Thermal Infrared Pedestrian Detection | LLVIP | YoloV5 | https://arxiv.org/abs/2108.10831v4 | AP | 0.670 |
Autonomous Vehicles > Pedestrian Detection > Thermal Infrared Pedestrian Detection | LLVIP | YoloV3 | https://arxiv.org/abs/2108.10831v4 | AP | 0.582 |
Autonomous Vehicles > Lane Detection | tvtLane | SCNN_UNet_Attention_PL* | https://arxiv.org/abs/2305.17271v2 | F1 | 0.924 |
Autonomous Vehicles > Lane Detection | CurveLanes | 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 | 88.47 |
Autonomous Vehicles > Lane Detection | CurveLanes | 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 | 88.23 |
Autonomous Vehicles > Lane Detection | CurveLanes | 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 | 87.99 |
Autonomous Vehicles > Lane Detection | CurveLanes | CANet-L | https://arxiv.org/abs/2304.11546v1 | F1 score | 87.87 |
Autonomous Vehicles > Lane Detection | CurveLanes | CANet-L | https://arxiv.org/abs/2304.11546v1 | Precision | 91.69 |
Autonomous Vehicles > Lane Detection | CurveLanes | CLRNetV2 (ResNet101) | https://ieeexplore.ieee.org/abstract/document/10930685 | F1 score | 87.81 |
Autonomous Vehicles > Lane Detection | CurveLanes | CANet-M | https://arxiv.org/abs/2304.11546v1 | F1 score | 87.19 |
Autonomous Vehicles > Lane Detection | CurveLanes | CANet-M | https://arxiv.org/abs/2304.11546v1 | Precision | 91.53 |
Autonomous Vehicles > Lane Detection | CurveLanes | CANet-M | https://arxiv.org/abs/2304.11546v1 | Recall | 83.25 |
Autonomous Vehicles > Lane Detection | CurveLanes | CANet-M | https://arxiv.org/abs/2304.11546v1 | GFLOPs | 22.6 |
Autonomous Vehicles > Lane Detection | CurveLanes | CANet-S | https://arxiv.org/abs/2304.11546v1 | F1 score | 86.57 |
Autonomous Vehicles > Lane Detection | CurveLanes | CANet-S | https://arxiv.org/abs/2304.11546v1 | Precision | 91.37 |
Autonomous Vehicles > Lane Detection | CurveLanes | CANet-S | https://arxiv.org/abs/2304.11546v1 | Recall | 82.25 |
Autonomous Vehicles > Lane Detection | CurveLanes | CANet-S | https://arxiv.org/abs/2304.11546v1 | GFLOPs | 13.1 |
Autonomous Vehicles > Lane Detection | CurveLanes | CLRerNet-DLA34 | https://arxiv.org/abs/2305.08366v1 | F1 score | 86.47 |
Autonomous Vehicles > Lane Detection | CurveLanes | CLRerNet-DLA34 | https://arxiv.org/abs/2305.08366v1 | Precision | 91.66 |
Autonomous Vehicles > Lane Detection | CurveLanes | CLRerNet-DLA34 | https://arxiv.org/abs/2305.08366v1 | Recall | 81.83 |
Autonomous Vehicles > Lane Detection | CurveLanes | CLRerNet-DLA34 | https://arxiv.org/abs/2305.08366v1 | GFLOPs | 18.4 |
Autonomous Vehicles > Lane Detection | CurveLanes | CLRNet-DLA34 | https://arxiv.org/abs/2305.08366v1 | F1 score | 86.1 |
Autonomous Vehicles > Lane Detection | CurveLanes | CLRNet-DLA34 | https://arxiv.org/abs/2305.08366v1 | Precision | 91.4 |
Autonomous Vehicles > Lane Detection | CurveLanes | CLRNet-DLA34 | https://arxiv.org/abs/2305.08366v1 | Recall | 81.39 |
Autonomous Vehicles > Lane Detection | CurveLanes | CLRNet-DLA34 | https://arxiv.org/abs/2305.08366v1 | GFLOPs | 18.4 |
Autonomous Vehicles > Lane Detection | CurveLanes | CondLaneNet-L(ResNet-101) | https://arxiv.org/abs/2105.05003v3 | F1 score | 86.10 |
Autonomous Vehicles > Lane Detection | CurveLanes | CondLaneNet-L(ResNet-101) | https://arxiv.org/abs/2105.05003v3 | Precision | 88.98 |
Autonomous Vehicles > Lane Detection | CurveLanes | CondLaneNet-L(ResNet-101) | https://arxiv.org/abs/2105.05003v3 | Recall | 83.41 |
Autonomous Vehicles > Lane Detection | CurveLanes | CondLaneNet-L(ResNet-101) | https://arxiv.org/abs/2105.05003v3 | GFLOPs | 44.9 |
Autonomous Vehicles > Lane Detection | CurveLanes | CondLaneNet-L(ResNet-101) | https://arxiv.org/abs/2105.05003v3 | FPS | 48 |
Autonomous Vehicles > Lane Detection | CurveLanes | CondLaneNet-M(ResNet-34) | https://arxiv.org/abs/2105.05003v3 | F1 score | 85.92 |
Autonomous Vehicles > Lane Detection | CurveLanes | CondLaneNet-M(ResNet-34) | https://arxiv.org/abs/2105.05003v3 | Precision | 88.29 |
Autonomous Vehicles > Lane Detection | CurveLanes | CondLaneNet-M(ResNet-34) | https://arxiv.org/abs/2105.05003v3 | Recall | 83.68 |
Autonomous Vehicles > Lane Detection | CurveLanes | CondLaneNet-M(ResNet-34) | https://arxiv.org/abs/2105.05003v3 | GFLOPs | 19.7 |
Autonomous Vehicles > Lane Detection | CurveLanes | CondLaneNet-M(ResNet-34) | https://arxiv.org/abs/2105.05003v3 | FPS | 109 |
Autonomous Vehicles > Lane Detection | CurveLanes | CondLaneNet-S(ResNet-18) | https://arxiv.org/abs/2105.05003v3 | F1 score | 85.09 |
Autonomous Vehicles > Lane Detection | CurveLanes | CondLaneNet-S(ResNet-18) | https://arxiv.org/abs/2105.05003v3 | Precision | 87.75 |
Autonomous Vehicles > Lane Detection | CurveLanes | CondLaneNet-S(ResNet-18) | https://arxiv.org/abs/2105.05003v3 | Recall | 82.58 |
Autonomous Vehicles > Lane Detection | CurveLanes | CondLaneNet-S(ResNet-18) | https://arxiv.org/abs/2105.05003v3 | GFLOPs | 10.3 |
Autonomous Vehicles > Lane Detection | CurveLanes | CondLaneNet-S(ResNet-18) | https://arxiv.org/abs/2105.05003v3 | FPS | 154 |
Autonomous Vehicles > Lane Detection | CurveLanes | CurveLane-L | https://arxiv.org/abs/2007.12147v1 | F1 score | 82.29 |
Autonomous Vehicles > Lane Detection | CurveLanes | CurveLane-L | https://arxiv.org/abs/2007.12147v1 | Precision | 91.11 |
Autonomous Vehicles > Lane Detection | CurveLanes | CurveLane-L | https://arxiv.org/abs/2007.12147v1 | Recall | 75.03 |
Autonomous Vehicles > Lane Detection | CurveLanes | CurveLane-L | https://arxiv.org/abs/2007.12147v1 | GFLOPs | 20.7 |
Autonomous Vehicles > Lane Detection | CurveLanes | CurveLane-M | https://arxiv.org/abs/2007.12147v1 | F1 score | 81.8 |
Autonomous Vehicles > Lane Detection | CurveLanes | CurveLane-M | https://arxiv.org/abs/2007.12147v1 | Precision | 93.49 |
Autonomous Vehicles > Lane Detection | CurveLanes | CurveLane-M | https://arxiv.org/abs/2007.12147v1 | Recall | 72.71 |
Autonomous Vehicles > Lane Detection | CurveLanes | CurveLane-M | https://arxiv.org/abs/2007.12147v1 | GFLOPs | 11.6 |
Autonomous Vehicles > Lane Detection | CurveLanes | CurveLane-S | https://arxiv.org/abs/2007.12147v1 | F1 score | 81.12 |
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