felixleungsc/paperswithcode-data-evaluation-tables

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 ⌀
Deblurring	HIDE (trained on GOPRO)	DeblurDiNAT-L	https://arxiv.org/abs/2403.13163v5	Params (M)	16.1
Deblurring	HIDE (trained on GOPRO)	Restormer	https://arxiv.org/abs/2111.09881v2	PSNR (sRGB)	31.22
Deblurring	HIDE (trained on GOPRO)	Restormer	https://arxiv.org/abs/2111.09881v2	SSIM (sRGB)	0.942
Deblurring	HIDE (trained on GOPRO)	Restormer	https://arxiv.org/abs/2111.09881v2	Params (M)	26.13
Deblurring	HIDE (trained on GOPRO)	MPRNet-TLC	https://arxiv.org/abs/2112.04491v4	PSNR (sRGB)	31.19
Deblurring	HIDE (trained on GOPRO)	MPRNet-TLC	https://arxiv.org/abs/2112.04491v4	SSIM (sRGB)	0.942
Deblurring	HIDE (trained on GOPRO)	MPRNet-TLC	https://arxiv.org/abs/2112.04491v4	Params (M)	20.1
Deblurring	HIDE (trained on GOPRO)	Stripformer	https://arxiv.org/abs/2204.04627v2	PSNR (sRGB)	31.03
Deblurring	HIDE (trained on GOPRO)	Stripformer	https://arxiv.org/abs/2204.04627v2	SSIM (sRGB)	0.94
Deblurring	HIDE (trained on GOPRO)	MPRNet	https://arxiv.org/abs/2102.02808v2	PSNR (sRGB)	30.96
Deblurring	HIDE (trained on GOPRO)	MPRNet	https://arxiv.org/abs/2102.02808v2	SSIM (sRGB)	0.939
Deblurring	HIDE (trained on GOPRO)	MPRNet	https://arxiv.org/abs/2102.02808v2	Params (M)	20.1
Deblurring	HIDE (trained on GOPRO)	Uformer-B	https://arxiv.org/abs/2106.03106v2	PSNR (sRGB)	30.83
Deblurring	HIDE (trained on GOPRO)	Uformer-B	https://arxiv.org/abs/2106.03106v2	SSIM (sRGB)	0.952
Deblurring	HIDE (trained on GOPRO)	Uformer-B	https://arxiv.org/abs/2106.03106v2	Params (M)	50.88
Deblurring	HIDE (trained on GOPRO)	BANet	https://arxiv.org/abs/2101.07518v4	PSNR (sRGB)	30.16
Deblurring	HIDE (trained on GOPRO)	BANet	https://arxiv.org/abs/2101.07518v4	SSIM (sRGB)	0.93
Deblurring	HIDE (trained on GOPRO)	Suin et al	null	PSNR (sRGB)	29.98
Deblurring	HIDE (trained on GOPRO)	Suin et al	null	SSIM (sRGB)	0.930
Deblurring	HIDE (trained on GOPRO)	MT-RNN	https://arxiv.org/abs/1911.07410v1	PSNR (sRGB)	29.15
Deblurring	HIDE (trained on GOPRO)	MT-RNN	https://arxiv.org/abs/1911.07410v1	SSIM (sRGB)	0.918
Deblurring	HIDE (trained on GOPRO)	MT-RNN	https://arxiv.org/abs/1911.07410v1	Params (M)	2.6
Deblurring	HIDE (trained on GOPRO)	Gao et al	null	PSNR (sRGB)	29.11
Deblurring	HIDE (trained on GOPRO)	Gao et al	null	SSIM (sRGB)	0.913
Deblurring	HIDE (trained on GOPRO)	DMPHN	http://arxiv.org/abs/1904.03468v1	PSNR (sRGB)	29.09
Deblurring	HIDE (trained on GOPRO)	DMPHN	http://arxiv.org/abs/1904.03468v1	SSIM (sRGB)	0.924
Deblurring	HIDE (trained on GOPRO)	DMPHN	http://arxiv.org/abs/1904.03468v1	Params (M)	7.23
Deblurring	HIDE (trained on GOPRO)	DBGAN	https://arxiv.org/abs/2004.01860v2	PSNR (sRGB)	28.94
Deblurring	HIDE (trained on GOPRO)	DBGAN	https://arxiv.org/abs/2004.01860v2	SSIM (sRGB)	0.915
Deblurring	HIDE (trained on GOPRO)	SRN	http://arxiv.org/abs/1802.01770v1	PSNR (sRGB)	28.36
Deblurring	HIDE (trained on GOPRO)	SRN	http://arxiv.org/abs/1802.01770v1	SSIM (sRGB)	0.915
Deblurring	HIDE (trained on GOPRO)	SRN	http://arxiv.org/abs/1802.01770v1	Params (M)	8.06
Deblurring	HIDE (trained on GOPRO)	Nah et al	http://arxiv.org/abs/1612.02177v2	PSNR (sRGB)	25.73
Deblurring	RSBlur	MLWNet	https://arxiv.org/abs/2401.00027v2	Average PSNR	34.94
Deblurring	RSBlur	MLWNet	https://arxiv.org/abs/2401.00027v2	SSIM	0.880
Deblurring	RSBlur	SegDeblur	https://arxiv.org/abs/2404.12168v1	Average PSNR	34.63
Deblurring	RSBlur	SFNet	https://openreview.net/forum?id=tyZ1ChGZIKO	Average PSNR	34.35
Deblurring	RSBlur	FSNet	https://ieeexplore.ieee.org/document/10310164	Average PSNR	34.31
Deblurring	RSBlur	IRNext	https://openreview.net/forum?id=MZkbgahv4a	Average PSNR	34.08
Deblurring	RSBlur	ConvIR	https://ieeexplore.ieee.org/abstract/document/10571568	Average PSNR	34.06
Deblurring	RSBlur	Uformer-B	https://arxiv.org/abs/2106.03106v2	Average PSNR	33.98
Deblurring	RSBlur	Restormer	https://arxiv.org/abs/2111.09881v2	Average PSNR	33.69
Deblurring	RSBlur	MPRNet	https://arxiv.org/abs/2102.02808v2	Average PSNR	33.61
Deblurring	RSBlur	MIMO-UNet+	https://arxiv.org/abs/2108.05054v2	Average PSNR	33.37
Deblurring	RSBlur	MIMO-UNet	https://arxiv.org/abs/2108.05054v2	Average PSNR	32.73
Deblurring	RSBlur	SRN-Deblur	http://arxiv.org/abs/1802.01770v1	Average PSNR	32.53
Deblurring	RSBlur (trained on synthetic)	MIMO-UNet + Realistic blur	https://arxiv.org/abs/2202.08771v3	Average PSNR	32.08
Deblurring	RSBlur (trained on synthetic)	SRN-Deblur + Realistic blur	https://arxiv.org/abs/2202.08771v3	Average PSNR	32.06
Structured Prediction	MNIST	CVAE	http://papers.nips.cc/paper/5775-learning-structured-output-representation-using-deep-conditional-generative-models	Negative CLL	71.8
Trajectory Prediction	ETH	Social-Implicit	https://arxiv.org/abs/2203.03057v2	Avg AMD/AMV 8/12	0.90
Trajectory Prediction	ETH	Trajectron++	https://arxiv.org/abs/2001.03093v5	Avg AMD/AMV 8/12	1.01
Trajectory Prediction	ETH	Social-STGCNN	https://arxiv.org/abs/2002.11927v3	Avg AMD/AMV 8/12	1.26
Trajectory Prediction	ETH	Social-GAN	http://arxiv.org/abs/1803.10892v1	Avg AMD/AMV 8/12	1.42
Trajectory Prediction	ETH	ExpertTraj	http://openaccess.thecvf.com//content/ICCV2021/html/Zhao_Where_Are_You_Heading_Dynamic_Trajectory_Prediction_With_Expert_Goal_ICCV_2021_paper.html	Avg AMD/AMV 8/12	19.20
Trajectory Prediction	Hotel BIWI Walking Pedestrians dataset	Social Ways	http://arxiv.org/abs/1904.09507v2	ADE-8/12	0.39
Trajectory Prediction	JAAD	SGNet	https://arxiv.org/abs/2103.14107v3	MSE(0.5)	82
Trajectory Prediction	JAAD	SGNet	https://arxiv.org/abs/2103.14107v3	MSE(1.0)	328
Trajectory Prediction	JAAD	SGNet	https://arxiv.org/abs/2103.14107v3	MSE(1.5)	1049
Trajectory Prediction	JAAD	SGNet	https://arxiv.org/abs/2103.14107v3	C_MSE(1.5)	996
Trajectory Prediction	JAAD	SGNet	https://arxiv.org/abs/2103.14107v3	CF_MSE(1.5)	4076
Trajectory Prediction	JAAD	BiTrap-D	https://arxiv.org/abs/2007.14558v2	MSE(0.5)	93
Trajectory Prediction	JAAD	BiTrap-D	https://arxiv.org/abs/2007.14558v2	MSE(1.0)	378
Trajectory Prediction	JAAD	BiTrap-D	https://arxiv.org/abs/2007.14558v2	MSE(1.5)	1206
Trajectory Prediction	JAAD	BiTrap-D	https://arxiv.org/abs/2007.14558v2	C_MSE(1.5)	1105
Trajectory Prediction	JAAD	BiTrap-D	https://arxiv.org/abs/2007.14558v2	CF_MSE(1.5)	4565
Trajectory Prediction	JAAD	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)	110
Trajectory Prediction	JAAD	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)	399
Trajectory Prediction	JAAD	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)	1280
Trajectory Prediction	JAAD	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)	1183
Trajectory Prediction	JAAD	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)	4780
Trajectory Prediction	JAAD	FOL-X	https://arxiv.org/abs/1903.00618v4	MSE(0.5)	147
Trajectory Prediction	JAAD	FOL-X	https://arxiv.org/abs/1903.00618v4	MSE(1.0)	484
Trajectory Prediction	JAAD	FOL-X	https://arxiv.org/abs/1903.00618v4	MSE(1.5)	1374
Trajectory Prediction	JAAD	FOL-X	https://arxiv.org/abs/1903.00618v4	C_MSE(1.5)	1290
Trajectory Prediction	JAAD	FOL-X	https://arxiv.org/abs/1903.00618v4	CF_MSE(1.5)	4924
Trajectory Prediction	JAAD	Bayesian-LSTM	http://arxiv.org/abs/1711.09026v2	MSE(0.5)	159
Trajectory Prediction	JAAD	Bayesian-LSTM	http://arxiv.org/abs/1711.09026v2	MSE(1.0)	539
Trajectory Prediction	JAAD	Bayesian-LSTM	http://arxiv.org/abs/1711.09026v2	MSE(1.5)	1535
Trajectory Prediction	JAAD	Bayesian-LSTM	http://arxiv.org/abs/1711.09026v2	C_MSE(1.5)	1447
Trajectory Prediction	JAAD	Bayesian-LSTM	http://arxiv.org/abs/1711.09026v2	CF_MSE(1.5)	5615
Trajectory Prediction	Argoverse2	HeteroGCN	https://arxiv.org/abs/2303.04364v1	minADE (K=6)	0.69
Trajectory Prediction	Argoverse2	HeteroGCN	https://arxiv.org/abs/2303.04364v1	minFDE (K=6)	1.34
Trajectory Prediction	Argoverse2	HeteroGCN	https://arxiv.org/abs/2303.04364v1	MR (K=6)	0.18
Trajectory Prediction	Argoverse2	HeteroGCN	https://arxiv.org/abs/2303.04364v1	brier-minFDE (K=6)	1.90
Trajectory Prediction	STATS SportVu NBA [ATK]	DAG-Net	https://arxiv.org/abs/2005.12661v2	ADE	9.18
Trajectory Prediction	STATS SportVu NBA [ATK]	DAG-Net	https://arxiv.org/abs/2005.12661v2	FDE	13.54
Trajectory Prediction	Apolloscape Trajectory	Trafficpredict	http://arxiv.org/abs/1811.02146v5	ADE	8.5881
Trajectory Prediction	HEV-I	SGNet	https://arxiv.org/abs/2103.14107v3	ADE(0.5)	6.28
Trajectory Prediction	HEV-I	SGNet	https://arxiv.org/abs/2103.14107v3	ADE(1.0)	11.35
Trajectory Prediction	HEV-I	SGNet	https://arxiv.org/abs/2103.14107v3	ADE(1.5)	18.27
Trajectory Prediction	HEV-I	SGNet	https://arxiv.org/abs/2103.14107v3	FDE(1.5)	39.86
Trajectory Prediction	HEV-I	SGNet	https://arxiv.org/abs/2103.14107v3	FIOU(1.5)	0.63
Trajectory Prediction	HEV-I	FOL-X	https://arxiv.org/abs/1903.00618v4	ADE(0.5)	6.70
Trajectory Prediction	HEV-I	FOL-X	https://arxiv.org/abs/1903.00618v4	ADE(1.0)	12.60
Trajectory Prediction	HEV-I	FOL-X	https://arxiv.org/abs/1903.00618v4	ADE(1.5)	20.40
Trajectory Prediction	HEV-I	FOL-X	https://arxiv.org/abs/1903.00618v4	FDE(1.5)	44.10
Trajectory Prediction	HEV-I	FOL-X	https://arxiv.org/abs/1903.00618v4	FIOU(1.5)	0.61
Trajectory Prediction	ApolloScape	SpectralCows	https://arxiv.org/abs/1912.01118v1	ADE	0.005
Trajectory Prediction	ApolloScape	rule-based	https://arxiv.org/abs/2010.12007v2	FDE	5.992
Trajectory Prediction	NGSIM	Pishgu	https://arxiv.org/abs/2210.08057v3	ADE	0.88

Deblurring

HIDE (trained on GOPRO)

DeblurDiNAT-L

https://arxiv.org/abs/2403.13163v5

Params (M)

16.1

Deblurring

HIDE (trained on GOPRO)

Restormer

https://arxiv.org/abs/2111.09881v2

PSNR (sRGB)

31.22

Deblurring

HIDE (trained on GOPRO)

Restormer

https://arxiv.org/abs/2111.09881v2

SSIM (sRGB)

0.942

Deblurring

HIDE (trained on GOPRO)

Restormer

https://arxiv.org/abs/2111.09881v2

Params (M)

26.13

Deblurring

HIDE (trained on GOPRO)

MPRNet-TLC

https://arxiv.org/abs/2112.04491v4

PSNR (sRGB)

31.19

Deblurring

HIDE (trained on GOPRO)

MPRNet-TLC

https://arxiv.org/abs/2112.04491v4

SSIM (sRGB)

0.942

Deblurring

HIDE (trained on GOPRO)

MPRNet-TLC

https://arxiv.org/abs/2112.04491v4

Params (M)

20.1

Deblurring

HIDE (trained on GOPRO)

Stripformer

https://arxiv.org/abs/2204.04627v2

PSNR (sRGB)

31.03

Deblurring

HIDE (trained on GOPRO)

Stripformer

https://arxiv.org/abs/2204.04627v2

SSIM (sRGB)

0.94

Deblurring

HIDE (trained on GOPRO)

MPRNet

https://arxiv.org/abs/2102.02808v2

PSNR (sRGB)

30.96

Deblurring

HIDE (trained on GOPRO)

MPRNet

https://arxiv.org/abs/2102.02808v2

SSIM (sRGB)

0.939

Deblurring

HIDE (trained on GOPRO)

MPRNet

https://arxiv.org/abs/2102.02808v2

Params (M)

20.1

Deblurring

HIDE (trained on GOPRO)

Uformer-B

https://arxiv.org/abs/2106.03106v2

PSNR (sRGB)

30.83

Deblurring

HIDE (trained on GOPRO)

Uformer-B

https://arxiv.org/abs/2106.03106v2

SSIM (sRGB)

0.952

Deblurring

HIDE (trained on GOPRO)

Uformer-B

https://arxiv.org/abs/2106.03106v2

Params (M)

50.88

Deblurring

HIDE (trained on GOPRO)

BANet

https://arxiv.org/abs/2101.07518v4

PSNR (sRGB)

30.16

Deblurring

HIDE (trained on GOPRO)

BANet

https://arxiv.org/abs/2101.07518v4

SSIM (sRGB)

0.93

Deblurring

HIDE (trained on GOPRO)

Suin et al

null

PSNR (sRGB)

29.98

Deblurring

HIDE (trained on GOPRO)

Suin et al

null

SSIM (sRGB)

0.930

Deblurring

HIDE (trained on GOPRO)

MT-RNN

https://arxiv.org/abs/1911.07410v1

PSNR (sRGB)

29.15

Deblurring

HIDE (trained on GOPRO)

MT-RNN

https://arxiv.org/abs/1911.07410v1

SSIM (sRGB)

0.918

Deblurring

HIDE (trained on GOPRO)

MT-RNN

https://arxiv.org/abs/1911.07410v1

Params (M)

2.6

Deblurring

HIDE (trained on GOPRO)

Gao et al

null

PSNR (sRGB)

29.11

Deblurring

HIDE (trained on GOPRO)

Gao et al

null

SSIM (sRGB)

0.913

Deblurring

HIDE (trained on GOPRO)

DMPHN

http://arxiv.org/abs/1904.03468v1

PSNR (sRGB)

29.09

Deblurring

HIDE (trained on GOPRO)

DMPHN

http://arxiv.org/abs/1904.03468v1

SSIM (sRGB)

0.924

Deblurring

HIDE (trained on GOPRO)

DMPHN

http://arxiv.org/abs/1904.03468v1

Params (M)

7.23

Deblurring

HIDE (trained on GOPRO)

DBGAN

https://arxiv.org/abs/2004.01860v2

PSNR (sRGB)

28.94

Deblurring

HIDE (trained on GOPRO)

DBGAN

https://arxiv.org/abs/2004.01860v2

SSIM (sRGB)

0.915

Deblurring

HIDE (trained on GOPRO)

SRN

http://arxiv.org/abs/1802.01770v1

PSNR (sRGB)

28.36

Deblurring

HIDE (trained on GOPRO)

SRN

http://arxiv.org/abs/1802.01770v1

SSIM (sRGB)

0.915

Deblurring

HIDE (trained on GOPRO)

SRN

http://arxiv.org/abs/1802.01770v1

Params (M)

8.06

Deblurring

HIDE (trained on GOPRO)

Nah et al

http://arxiv.org/abs/1612.02177v2

PSNR (sRGB)

25.73

Deblurring

RSBlur

MLWNet

https://arxiv.org/abs/2401.00027v2

Average PSNR

34.94

Deblurring

RSBlur

MLWNet

https://arxiv.org/abs/2401.00027v2

SSIM

0.880

Deblurring

RSBlur

SegDeblur

https://arxiv.org/abs/2404.12168v1

Average PSNR

34.63

Deblurring

RSBlur

SFNet

https://openreview.net/forum?id=tyZ1ChGZIKO

Average PSNR

34.35

Deblurring

RSBlur

FSNet

https://ieeexplore.ieee.org/document/10310164

Average PSNR

34.31

Deblurring

RSBlur

IRNext

https://openreview.net/forum?id=MZkbgahv4a

Average PSNR

34.08

Deblurring

RSBlur

ConvIR

https://ieeexplore.ieee.org/abstract/document/10571568

Average PSNR

34.06

Deblurring

RSBlur

Uformer-B

https://arxiv.org/abs/2106.03106v2

Average PSNR

33.98

Deblurring

RSBlur

Restormer

https://arxiv.org/abs/2111.09881v2

Average PSNR

33.69

Deblurring

RSBlur

MPRNet

https://arxiv.org/abs/2102.02808v2

Average PSNR

33.61

Deblurring

RSBlur

MIMO-UNet+

https://arxiv.org/abs/2108.05054v2

Average PSNR

33.37

Deblurring

RSBlur

MIMO-UNet

https://arxiv.org/abs/2108.05054v2

Average PSNR

32.73

Deblurring

RSBlur

SRN-Deblur

http://arxiv.org/abs/1802.01770v1

Average PSNR

32.53

Deblurring

RSBlur (trained on synthetic)

MIMO-UNet + Realistic blur

https://arxiv.org/abs/2202.08771v3

Average PSNR

32.08

Deblurring

RSBlur (trained on synthetic)

SRN-Deblur + Realistic blur

https://arxiv.org/abs/2202.08771v3

Average PSNR

32.06

Structured Prediction

MNIST

CVAE

http://papers.nips.cc/paper/5775-learning-structured-output-representation-using-deep-conditional-generative-models

Negative CLL

71.8

Trajectory Prediction

ETH

Social-Implicit

https://arxiv.org/abs/2203.03057v2

Avg AMD/AMV 8/12

0.90

Trajectory Prediction

ETH

Trajectron++

https://arxiv.org/abs/2001.03093v5

Avg AMD/AMV 8/12

1.01

Trajectory Prediction

ETH

Social-STGCNN

https://arxiv.org/abs/2002.11927v3

Avg AMD/AMV 8/12

1.26

Trajectory Prediction

ETH

Social-GAN

http://arxiv.org/abs/1803.10892v1

Avg AMD/AMV 8/12

1.42

Trajectory Prediction

ETH

ExpertTraj

http://openaccess.thecvf.com//content/ICCV2021/html/Zhao_Where_Are_You_Heading_Dynamic_Trajectory_Prediction_With_Expert_Goal_ICCV_2021_paper.html

Avg AMD/AMV 8/12

19.20

Trajectory Prediction

Hotel BIWI Walking Pedestrians dataset

Social Ways

http://arxiv.org/abs/1904.09507v2

ADE-8/12

0.39

Trajectory Prediction

JAAD

SGNet

https://arxiv.org/abs/2103.14107v3

MSE(0.5)

82

Trajectory Prediction

JAAD

SGNet

https://arxiv.org/abs/2103.14107v3

MSE(1.0)

328

Trajectory Prediction

JAAD

SGNet

https://arxiv.org/abs/2103.14107v3

MSE(1.5)

1049

Trajectory Prediction

JAAD

SGNet

https://arxiv.org/abs/2103.14107v3

C_MSE(1.5)

996

Trajectory Prediction

JAAD

SGNet

https://arxiv.org/abs/2103.14107v3

CF_MSE(1.5)

4076

Trajectory Prediction

JAAD

BiTrap-D

https://arxiv.org/abs/2007.14558v2

MSE(0.5)

93

Trajectory Prediction

JAAD

BiTrap-D

https://arxiv.org/abs/2007.14558v2

MSE(1.0)

378

Trajectory Prediction

JAAD

BiTrap-D

https://arxiv.org/abs/2007.14558v2

MSE(1.5)

1206

Trajectory Prediction

JAAD

BiTrap-D

https://arxiv.org/abs/2007.14558v2

C_MSE(1.5)

1105

Trajectory Prediction

JAAD

BiTrap-D

https://arxiv.org/abs/2007.14558v2

CF_MSE(1.5)

4565

Trajectory Prediction

JAAD

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)

110

Trajectory Prediction

JAAD

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)

399

Trajectory Prediction

JAAD

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)

1280

Trajectory Prediction

JAAD

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)

1183

Trajectory Prediction

JAAD

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)

4780

Trajectory Prediction

JAAD

FOL-X

https://arxiv.org/abs/1903.00618v4

MSE(0.5)

147

Trajectory Prediction

JAAD

FOL-X

https://arxiv.org/abs/1903.00618v4

MSE(1.0)

484

Trajectory Prediction

JAAD

FOL-X

https://arxiv.org/abs/1903.00618v4

MSE(1.5)

1374

Trajectory Prediction

JAAD

FOL-X

https://arxiv.org/abs/1903.00618v4

C_MSE(1.5)

1290

Trajectory Prediction

JAAD

FOL-X

https://arxiv.org/abs/1903.00618v4

CF_MSE(1.5)

4924

Trajectory Prediction

JAAD

Bayesian-LSTM

http://arxiv.org/abs/1711.09026v2

MSE(0.5)

159

Trajectory Prediction

JAAD

Bayesian-LSTM

http://arxiv.org/abs/1711.09026v2

MSE(1.0)

539

Trajectory Prediction

JAAD

Bayesian-LSTM

http://arxiv.org/abs/1711.09026v2

MSE(1.5)

1535

Trajectory Prediction

JAAD

Bayesian-LSTM

http://arxiv.org/abs/1711.09026v2

C_MSE(1.5)

1447

Trajectory Prediction

JAAD

Bayesian-LSTM

http://arxiv.org/abs/1711.09026v2

CF_MSE(1.5)

5615

Trajectory Prediction

Argoverse2

HeteroGCN

https://arxiv.org/abs/2303.04364v1

minADE (K=6)

0.69

Trajectory Prediction

Argoverse2

HeteroGCN

https://arxiv.org/abs/2303.04364v1

minFDE (K=6)

1.34

Trajectory Prediction

Argoverse2

HeteroGCN

https://arxiv.org/abs/2303.04364v1

MR (K=6)

0.18

Trajectory Prediction

Argoverse2

HeteroGCN

https://arxiv.org/abs/2303.04364v1

brier-minFDE (K=6)

1.90

Trajectory Prediction

STATS SportVu NBA [ATK]

DAG-Net

https://arxiv.org/abs/2005.12661v2

ADE

9.18

Trajectory Prediction

STATS SportVu NBA [ATK]

DAG-Net

https://arxiv.org/abs/2005.12661v2

FDE

13.54

Trajectory Prediction

Apolloscape Trajectory

Trafficpredict

http://arxiv.org/abs/1811.02146v5

ADE

8.5881

Trajectory Prediction

HEV-I

SGNet

https://arxiv.org/abs/2103.14107v3

ADE(0.5)

6.28

Trajectory Prediction

HEV-I

SGNet

https://arxiv.org/abs/2103.14107v3

ADE(1.0)

11.35

Trajectory Prediction

HEV-I

SGNet

https://arxiv.org/abs/2103.14107v3

ADE(1.5)

18.27

Trajectory Prediction

HEV-I

SGNet

https://arxiv.org/abs/2103.14107v3

FDE(1.5)

39.86

Trajectory Prediction

HEV-I

SGNet

https://arxiv.org/abs/2103.14107v3

FIOU(1.5)

0.63

Trajectory Prediction

HEV-I

FOL-X

https://arxiv.org/abs/1903.00618v4

ADE(0.5)

6.70

Trajectory Prediction

HEV-I

FOL-X

https://arxiv.org/abs/1903.00618v4

ADE(1.0)

12.60

Trajectory Prediction

HEV-I

FOL-X

https://arxiv.org/abs/1903.00618v4

ADE(1.5)

20.40

Trajectory Prediction

HEV-I

FOL-X

https://arxiv.org/abs/1903.00618v4

FDE(1.5)

44.10

Trajectory Prediction

HEV-I

FOL-X

https://arxiv.org/abs/1903.00618v4

FIOU(1.5)

0.61

Trajectory Prediction

ApolloScape

SpectralCows

https://arxiv.org/abs/1912.01118v1

ADE

0.005

Trajectory Prediction

ApolloScape

rule-based

https://arxiv.org/abs/2010.12007v2

FDE

5.992

Trajectory Prediction

NGSIM

Pishgu

https://arxiv.org/abs/2210.08057v3

ADE

0.88