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 ⌀ |
|---|---|---|---|---|---|
Trajectory Prediction | nuScenes | Physics Oracle | null | MinADE_5 | 3.7 |
Trajectory Prediction | nuScenes | Physics Oracle | null | MinADE_10 | 3.7 |
Trajectory Prediction | nuScenes | Physics Oracle | null | MissRateTopK_2_5 | 0.88 |
Trajectory Prediction | nuScenes | Physics Oracle | null | MissRateTopK_2_10 | 0.88 |
Trajectory Prediction | nuScenes | Physics Oracle | null | MinFDE_1 | 9.09 |
Trajectory Prediction | nuScenes | Physics Oracle | null | OffRoadRate | 0.12 |
Trajectory Prediction | nuScenes | xli4217 | null | MinADE_5 | 4.46 |
Trajectory Prediction | nuScenes | xli4217 | null | MinADE_10 | 4.46 |
Trajectory Prediction | nuScenes | xli4217 | null | MissRateTopK_2_5 | 0.91 |
Trajectory Prediction | nuScenes | xli4217 | null | MissRateTopK_2_10 | 0.91 |
Trajectory Prediction | nuScenes | xli4217 | null | MinFDE_1 | 9.52 |
Trajectory Prediction | nuScenes | xli4217 | null | OffRoadRate | 0.07 |
Trajectory Prediction | nuScenes | CoverNet | null | MinADE_5 | 4.61 |
Trajectory Prediction | nuScenes | CoverNet | null | MinADE_10 | 4.61 |
Trajectory Prediction | nuScenes | CoverNet | null | MissRateTopK_2_5 | 0.91 |
Trajectory Prediction | nuScenes | CoverNet | null | MissRateTopK_2_10 | 0.91 |
Trajectory Prediction | nuScenes | CoverNet | null | MinFDE_1 | 11.21 |
Trajectory Prediction | nuScenes | CoverNet | null | OffRoadRate | 0.14 |
Trajectory Prediction | ForkingPaths | Multiverse | https://arxiv.org/abs/1912.06445v3 | ADE | 168.9 |
Trajectory Prediction | TrajAir: A General Aviation Trajectory Dataset | TrajAirNet | https://arxiv.org/abs/2109.15158v2 | ADE (in world coordinates) | 0.73 |
Trajectory Prediction | TrajAir: A General Aviation Trajectory Dataset | TrajAirNet | https://arxiv.org/abs/2109.15158v2 | FDE (in world coordinates) | 1.42 |
Trajectory Prediction | UCY | Social-Implicit | https://arxiv.org/abs/2203.03057v2 | Avg AMD/AMV 8/12 | 0.90 |
Trajectory Prediction | INTERACTION Dataset - Validation | ITRA | https://arxiv.org/abs/2104.11212v1 | minADE6 | 0.17 |
Trajectory Prediction | INTERACTION Dataset - Validation | ITRA | https://arxiv.org/abs/2104.11212v1 | minFDE6 | 0.49 |
Trajectory Prediction | INTERACTION Dataset - Validation | TNT | https://arxiv.org/abs/2008.08294v2 | minADE6 | 0.21 |
Trajectory Prediction | INTERACTION Dataset - Validation | TNT | https://arxiv.org/abs/2008.08294v2 | minFDE6 | 0.67 |
Trajectory Prediction | INTERACTION Dataset - Validation | DESIRE | http://arxiv.org/abs/1704.04394v1 | minADE6 | 0.32 |
Trajectory Prediction | INTERACTION Dataset - Validation | DESIRE | http://arxiv.org/abs/1704.04394v1 | minFDE6 | 0.88 |
Trajectory Prediction | INTERACTION Dataset - Validation | GOHOME | https://arxiv.org/abs/2109.01827v4 | minFDE6 | 0.45 |
Trajectory Prediction | INTERACTION Dataset - Validation | GOHOME | https://arxiv.org/abs/2109.01827v4 | minFDE1 | 0.61 |
Trajectory Prediction | PROX | Skeleton-Graph | https://arxiv.org/abs/2109.10257v2 | FDE | 288 |
Trajectory Prediction | PROX | Skeleton-Graph | https://arxiv.org/abs/2109.10257v2 | ADE | 280 |
Trajectory Prediction | PROX | Skeleton-Graph | https://arxiv.org/abs/2109.10257v2 | STB | 6 |
Trajectory Prediction | PAID | DESIRE | http://arxiv.org/abs/1704.04394v1 | minFDE3 | 0.59 |
Trajectory Prediction | PAID | DESIRE | http://arxiv.org/abs/1704.04394v1 | minADE3 | 0.29 |
Trajectory Prediction | PAID | MultiPath | https://arxiv.org/abs/1910.05449v1 | minFDE3 | 0.43 |
Trajectory Prediction | PAID | MultiPath | https://arxiv.org/abs/1910.05449v1 | minADE3 | 0.23 |
Trajectory Prediction | PAID | TNT | https://arxiv.org/abs/2008.08294v2 | minFDE3 | 0.32 |
Trajectory Prediction | PAID | TNT | https://arxiv.org/abs/2008.08294v2 | minADE3 | 0.18 |
Trajectory Prediction | ActEV | Pishgu | https://arxiv.org/abs/2210.08057v3 | ADE-8/12 | 14.11 |
Trajectory Prediction | ActEV | Pishgu | https://arxiv.org/abs/2210.08057v3 | FDE-8/12 | 27.96 |
Trajectory Prediction | ActEV | SimAug | https://arxiv.org/abs/2004.02022v2 | ADE-8/12 | 17.96 |
Trajectory Prediction | ActEV | SimAug | https://arxiv.org/abs/2004.02022v2 | FDE-8/12 | 34.68 |
Trajectory Prediction | ActEV | Next | https://arxiv.org/abs/1902.03748v3 | ADE-8/12 | 17.99 |
Trajectory Prediction | ActEV | Next | https://arxiv.org/abs/1902.03748v3 | FDE-8/12 | 37.24 |
Trajectory Prediction | ActEV | Multiverse | https://arxiv.org/abs/1912.06445v3 | ADE-8/12 | 18.51 |
Trajectory Prediction | ActEV | Multiverse | https://arxiv.org/abs/1912.06445v3 | FDE-8/12 | 35.84 |
Trajectory Prediction | TrajNet++ | Social-NCE + Social-LSTM | https://arxiv.org/abs/2012.11717v3 | FDE | 1.14 |
Trajectory Prediction | TrajNet++ | Social-NCE + Social-LSTM | https://arxiv.org/abs/2012.11717v3 | COL | 5.31 |
Trajectory Prediction | TrajNet++ | U-LSTM + Social Pooling | https://arxiv.org/abs/2106.04419v2 | FDE | 1.150 |
Trajectory Prediction | TrajNet++ | U-LSTM + Social Pooling | https://arxiv.org/abs/2106.04419v2 | COL | 6.560 |
Trajectory Prediction | TrajNet++ | Social LSTM | https://arxiv.org/abs/2007.03639v3 | FDE | 1.17 |
Trajectory Prediction | TrajNet++ | Social LSTM | https://arxiv.org/abs/2007.03639v3 | COL | 7.59 |
Trajectory Prediction | PIE | SGNet | https://arxiv.org/abs/2103.14107v3 | MSE(0.5) | 34 |
Trajectory Prediction | PIE | SGNet | https://arxiv.org/abs/2103.14107v3 | MSE(1.0) | 133 |
Trajectory Prediction | PIE | SGNet | https://arxiv.org/abs/2103.14107v3 | MSE(1.5) | 442 |
Trajectory Prediction | PIE | SGNet | https://arxiv.org/abs/2103.14107v3 | C_MSE(1.5) | 413 |
Trajectory Prediction | PIE | SGNet | https://arxiv.org/abs/2103.14107v3 | CF_MSE(1.5) | 1761 |
Trajectory Prediction | PIE | Bitrap-D | https://arxiv.org/abs/2007.14558v2 | MSE(0.5) | 41 |
Trajectory Prediction | PIE | Bitrap-D | https://arxiv.org/abs/2007.14558v2 | MSE(1.0) | 161 |
Trajectory Prediction | PIE | Bitrap-D | https://arxiv.org/abs/2007.14558v2 | MSE(1.5) | 511 |
Trajectory Prediction | PIE | Bitrap-D | https://arxiv.org/abs/2007.14558v2 | C_MSE(1.5) | 481 |
Trajectory Prediction | PIE | Bitrap-D | https://arxiv.org/abs/2007.14558v2 | CF_MSE(1.5) | 1949 |
Trajectory Prediction | PIE | PIE_traj | http://openaccess.thecvf.com/content_ICCV_2019/html/Rasouli_PIE_A_Large-Scale_Dataset_and_Models_for_Pedestrian_Intention_Estimation_ICCV_2019_paper.html | MSE(0.5) | 58 |
Trajectory Prediction | PIE | PIE_traj | http://openaccess.thecvf.com/content_ICCV_2019/html/Rasouli_PIE_A_Large-Scale_Dataset_and_Models_for_Pedestrian_Intention_Estimation_ICCV_2019_paper.html | MSE(1.0) | 200 |
Trajectory Prediction | PIE | PIE_traj | http://openaccess.thecvf.com/content_ICCV_2019/html/Rasouli_PIE_A_Large-Scale_Dataset_and_Models_for_Pedestrian_Intention_Estimation_ICCV_2019_paper.html | MSE(1.5) | 636 |
Trajectory Prediction | PIE | PIE_traj | http://openaccess.thecvf.com/content_ICCV_2019/html/Rasouli_PIE_A_Large-Scale_Dataset_and_Models_for_Pedestrian_Intention_Estimation_ICCV_2019_paper.html | C_MSE(1.5) | 596 |
Trajectory Prediction | PIE | PIE_traj | http://openaccess.thecvf.com/content_ICCV_2019/html/Rasouli_PIE_A_Large-Scale_Dataset_and_Models_for_Pedestrian_Intention_Estimation_ICCV_2019_paper.html | CF_MSE(1.5) | 2477 |
Trajectory Prediction | PIE | FOL-X | https://arxiv.org/abs/1903.00618v4 | MSE(0.5) | 147 |
Trajectory Prediction | PIE | FOL-X | https://arxiv.org/abs/1903.00618v4 | MSE(1.0) | 484 |
Trajectory Prediction | PIE | FOL-X | https://arxiv.org/abs/1903.00618v4 | MSE(1.5) | 1374 |
Trajectory Prediction | PIE | FOL-X | https://arxiv.org/abs/1903.00618v4 | C_MSE(1.5) | 1290 |
Trajectory Prediction | PIE | FOL-X | https://arxiv.org/abs/1903.00618v4 | CF_MSE(1.5) | 4924 |
Trajectory Prediction | PIE | Bayesian-LSTM | http://arxiv.org/abs/1711.09026v2 | MSE(0.5) | 159 |
Trajectory Prediction | PIE | Bayesian-LSTM | http://arxiv.org/abs/1711.09026v2 | MSE(1.0) | 539 |
Trajectory Prediction | PIE | Bayesian-LSTM | http://arxiv.org/abs/1711.09026v2 | MSE(1.5) | 1535 |
Trajectory Prediction | PIE | Bayesian-LSTM | http://arxiv.org/abs/1711.09026v2 | C_MSE(1.5) | 1447 |
Trajectory Prediction | PIE | Bayesian-LSTM | http://arxiv.org/abs/1711.09026v2 | CF_MSE(1.5) | 5615 |
Trajectory Prediction | STATS SportVu NBA [DEF] | DAG-Net | https://arxiv.org/abs/2005.12661v2 | ADE | 7.01 |
Trajectory Prediction | STATS SportVu NBA [DEF] | DAG-Net | https://arxiv.org/abs/2005.12661v2 | FDE | 9.76 |
Trajectory Prediction > Trajectory Forecasting | Stanford Drone | SimAug | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/1850_ECCV_2020_paper.php | ADE-8/12 @K = 20 | 10.27 |
Trajectory Prediction > Trajectory Forecasting | TrajNet++ | Social NCE + Social LSTM | https://arxiv.org/abs/2012.11717v3 | FDE | 1.14 |
Trajectory Prediction > Trajectory Forecasting | TrajNet++ | Social NCE + Social LSTM | https://arxiv.org/abs/2012.11717v3 | COL | 5.31 |
Trajectory Prediction > Trajectory Forecasting | TrajNet++ | U-LSTM + Social Pooling | https://arxiv.org/abs/2106.04419v2 | FDE | 1.150 |
Trajectory Prediction > Trajectory Forecasting | TrajNet++ | U-LSTM + Social Pooling | https://arxiv.org/abs/2106.04419v2 | COL | 6.560 |
Trajectory Prediction > Trajectory Forecasting | TrajNet++ | Social LSTM | https://arxiv.org/abs/2007.03639v3 | FDE | 1.17 |
Trajectory Prediction > Trajectory Forecasting | TrajNet++ | Social LSTM | https://arxiv.org/abs/2007.03639v3 | COL | 7.59 |
Trajectory Prediction > Trajectory Forecasting | ActEV | SimAug | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/1850_ECCV_2020_paper.php | ADE-8/12 | 17.96 |
Trajectory Prediction > Trajectory Forecasting | ActEV | Next | https://arxiv.org/abs/1902.03748v3 | ADE-8/12 | 17.99 |
Trajectory Prediction > Trajectory Forecasting | ForkingPaths | Multiverse | https://arxiv.org/abs/1912.06445v3 | ADE | 168.9 |
Trajectory Prediction > Out-of-Sight Trajectory Prediction | Vi-Fi Multi-modal Dataset | OOSTraj | https://arxiv.org/abs/2404.02227v1 | SUM | 27.24 |
Trajectory Prediction > Out-of-Sight Trajectory Prediction | Vi-Fi Multi-modal Dataset | OOSTraj | https://arxiv.org/abs/2404.02227v1 | MSE-D | 13.42 |
Trajectory Prediction > Out-of-Sight Trajectory Prediction | Vi-Fi Multi-modal Dataset | OOSTraj | https://arxiv.org/abs/2404.02227v1 | MSE-P | 13.83 |
Trajectory Prediction > Out-of-Sight Trajectory Prediction | Vi-Fi Multi-modal Dataset | Transformer | https://arxiv.org/abs/2404.02227v1 | SUM | 28.33 |
Trajectory Prediction > Out-of-Sight Trajectory Prediction | Vi-Fi Multi-modal Dataset | Transformer | https://arxiv.org/abs/2404.02227v1 | MSE-D | 14.26 |
Trajectory Prediction > Out-of-Sight Trajectory Prediction | Vi-Fi Multi-modal Dataset | Transformer | https://arxiv.org/abs/2404.02227v1 | MSE-P | 14.08 |
Trajectory Prediction > Out-of-Sight Trajectory Prediction | Vi-Fi Multi-modal Dataset | RNN | https://arxiv.org/abs/2404.02227v1 | SUM | 31.61 |
Trajectory Prediction > Out-of-Sight Trajectory Prediction | Vi-Fi Multi-modal Dataset | RNN | https://arxiv.org/abs/2404.02227v1 | MSE-D | 15.92 |
Trajectory Prediction > Out-of-Sight Trajectory Prediction | Vi-Fi Multi-modal Dataset | RNN | https://arxiv.org/abs/2404.02227v1 | MSE-P | 15.69 |
Trajectory Prediction > Out-of-Sight Trajectory Prediction | Vi-Fi Multi-modal Dataset | GRU | https://arxiv.org/abs/2404.02227v1 | SUM | 57.34 |
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