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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