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 ⌀
16k > Object Detection > Open World Object Detection	COCO-OOD	unsniffer	https://arxiv.org/abs/2303.13769v3	unknown F1 score	0.479
16k > Object Detection > Open World Object Detection	COCO VOC to non-VOC	GOOD	https://arxiv.org/abs/2212.11720v3	AR100	39.7
16k > Object Detection > Open World Object Detection	COCO VOC to non-VOC	OLN-Box	https://arxiv.org/abs/2108.06753v1	AR100	33.4
16k > Object Detection > Open World Object Detection	PASCAL VOC 2007	ORE (MDef-DETR)	https://arxiv.org/abs/2111.11430v6	WI	0.0474
16k > Object Detection > Open World Object Detection	PASCAL VOC 2007	ORE (MDef-DETR)	https://arxiv.org/abs/2111.11430v6	A-OSE	7322
16k > Object Detection > Open World Object Detection	PASCAL VOC 2007	ORE (MDef-DETR)	https://arxiv.org/abs/2111.11430v6	MAP	64.03
16k > Object Detection > Open World Object Detection	PASCAL VOC 2007	ORE (MDef-DETR)	https://arxiv.org/abs/2111.11430v6	Unknown Recall	50.13
16k > Object Detection > Open World Object Detection	PASCAL VOC 2007	ORE	https://arxiv.org/abs/2103.02603v2	WI	0.02193
16k > Object Detection > Open World Object Detection	PASCAL VOC 2007	ORE	https://arxiv.org/abs/2103.02603v2	A-OSE	8234
16k > Object Detection > Open World Object Detection	PASCAL VOC 2007	ORE	https://arxiv.org/abs/2103.02603v2	MAP	56.34
16k > Object Detection > Open World Object Detection	PASCAL VOC 2007	ORE	https://arxiv.org/abs/2103.02603v2	Unknown Recall	14.40
16k > Object Detection > Medical Object Detection	DeepLesion	P3D	https://arxiv.org/abs/2201.01426v1	Sensitivity	88.55
16k > Object Detection > Medical Object Detection	DeepLesion	DKMA-ULD	https://arxiv.org/abs/2203.06886v1	Sensitivity	87.16
16k > Object Detection > Medical Object Detection	DeepLesion	AlignShift	https://arxiv.org/abs/2103.12277v1	Sensitivity	86.83
16k > Object Detection > Medical Object Detection	DeepLesion	MP3D	https://arxiv.org/abs/2012.08770v1	Sensitivity	86.74
16k > Object Detection > Medical Object Detection	DeepLesion	MELD	https://arxiv.org/abs/2005.13753v1	Sensitivity	86.6
16k > Object Detection > Medical Object Detection	DeepLesion	FCOS	https://arxiv.org/abs/2203.16074v1	Sensitivity	86.05
16k > Object Detection > Medical Object Detection	DeepLesion	MULAN	https://arxiv.org/abs/1908.04373v1	Sensitivity	85.22
16k > Object Detection > Medical Object Detection	DeepLesion	MVP Net	https://arxiv.org/abs/1909.04247v3	Sensitivity	83.64
16k > Object Detection > Medical Object Detection	DeepLesion	Improved RetinaNet	https://arxiv.org/abs/1906.02283v1	Sensitivity	82.36
16k > Object Detection > Medical Object Detection	DeepLesion	3DCE	http://arxiv.org/abs/1806.09648v2	Sensitivity	75.55
16k > Object Detection > Medical Object Detection	GRAZPEDWRI-DX	YOLOv8x	https://arxiv.org/abs/2407.12597v2	mAP	77.00
16k > Object Detection > Medical Object Detection	MoNuSeg 2018	CircleNet	https://arxiv.org/abs/2110.12093v1	Average-mAP	0.487
16k > Object Detection > Medical Object Detection	Barrett’s Esophagus	Attention-based model	https://arxiv.org/abs/1811.08513v2	Mean Accuracy	81%
16k > Object Detection > Medical Object Detection	Barrett’s Esophagus	Sliding Window	http://arxiv.org/abs/1703.02442v2	Mean Accuracy	74%
16k > Object Detection > Dense Object Detection	SKU-110K	RetailDet	https://arxiv.org/abs/2204.00298v4	AP	59.0
16k > Object Detection > Dense Object Detection	SKU-110K	Cascade-RCNN	https://arxiv.org/abs/2007.11946v3	AP	58.7
16k > Object Detection > Dense Object Detection	SKU-110K	SAPD	https://arxiv.org/abs/1911.12448v2	AP	55.7
16k > Object Detection > Dense Object Detection	SKU-110K	Soft-IoU + EM-Merger unit	http://arxiv.org/abs/1904.00853v3	AP	49.2
16k > Object Detection > Dense Object Detection	SKU-110K	RetinaNet	http://arxiv.org/abs/1708.02002v2	AP	45.5
16k > Object Detection > Dense Object Detection	SKU-110K	RetinaNet	http://arxiv.org/abs/1708.02002v2	AP75	.389
16k > Object Detection > Object Proposal Generation	PASCAL VOC 2012, 60 proposals per image	MDef-DETR	https://arxiv.org/abs/2111.11430v6	Average Recall	0.9126
16k > Object Detection > Object Proposal Generation	PASCAL VOC 2012, 60 proposals per image	Recurrent Pixel Embedding	http://arxiv.org/abs/1712.08273v1	Average Recall	0.814
16k > Object Detection > Object Proposal Generation	PASCAL VOC 2012, 60 proposals per image	inst-DML	http://arxiv.org/abs/1703.10277v1	Average Recall	0.667
16k > Object Detection > Object Proposal Generation	COCO (Common Objects in Context)	MDef-DETR (Off-the-shelf evaluation)	https://arxiv.org/abs/2111.11430v6	Average Recall	0.6503
16k > Object Detection > Head Detection	Rebar Head	WSMA-Seg (stack=2 ,base=40, depth=5)	https://arxiv.org/abs/1904.13300v3	F1	98.83%
16k > Object Detection > License Plate Detection	Common Voice Estonian	porshe	https://arxiv.org/abs/2206.09379v2	0S	big car
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv8+SE	https://arxiv.org/abs/2410.01031v2	F1-score	0.66
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv8+SE	https://arxiv.org/abs/2410.01031v2	AP50	67.07
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv8+GC	https://arxiv.org/abs/2407.03163v1	F1-score	0.66
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv8+GC	https://arxiv.org/abs/2407.03163v1	AP50	66.32
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv8+GC	https://arxiv.org/abs/2410.01031v2	F1-score	0.66
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv8+GC	https://arxiv.org/abs/2410.01031v2	AP50	66.32
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv8+GE	https://arxiv.org/abs/2410.01031v2	F1-score	0.64
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv8+GE	https://arxiv.org/abs/2410.01031v2	AP50	65.99
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv8+ResCBAM	https://arxiv.org/abs/2409.18826v1	F1-score	0.64
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv8+ResCBAM	https://arxiv.org/abs/2409.18826v1	AP50	65.8
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv8+ResCBAM	https://arxiv.org/abs/2402.09329v5	F1-score	0.64
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv8+ResCBAM	https://arxiv.org/abs/2402.09329v5	AP50	65.8
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv8+GCT	https://arxiv.org/abs/2410.01031v2	F1-score	0.64
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv8+GCT	https://arxiv.org/abs/2410.01031v2	AP50	65.67
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv9-E	https://arxiv.org/abs/2403.11249v2	F1-score	0.64
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv9-E	https://arxiv.org/abs/2403.11249v2	AP50	65.46
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv9-C	https://arxiv.org/abs/2403.11249v2	F1-score	0.64
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv9-C	https://arxiv.org/abs/2403.11249v2	AP50	65.31
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv8+ResGAM	https://arxiv.org/abs/2402.09329v5	F1-score	0.64
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv8+ResGAM	https://arxiv.org/abs/2402.09329v5	AP50	65.0
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv8+SA	https://arxiv.org/abs/2402.09329v5	F1-score	0.63
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv8+SA	https://arxiv.org/abs/2402.09329v5	AP50	64.3
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv8+ECA	https://arxiv.org/abs/2402.09329v5	F1-score	0.65
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv8+ECA	https://arxiv.org/abs/2402.09329v5	AP50	64.2
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv8+GAM	https://arxiv.org/abs/2402.09329v5	F1-score	0.65
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv8+GAM	https://arxiv.org/abs/2402.09329v5	AP50	64.2
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv8	https://arxiv.org/abs/2304.05071v5	F1-score	0.62
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv8	https://arxiv.org/abs/2304.05071v5	AP50	63.6
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv10-M	https://arxiv.org/abs/2407.15689v2	Fracture Sensitivity	92.5
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv8m	https://arxiv.org/abs/2407.12597v2	Fracture Sensitivity	92.00
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv7	https://arxiv.org/abs/2407.12597v2	Fracture Sensitivity	91.00
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv5s	https://arxiv.org/abs/2206.09379v2	Fracture Sensitivity	91.00
16k > Object Detection > Fracture detection	GRAZPEDWRI-DX	YOLOv6s	https://arxiv.org/abs/2206.09379v2	Fracture Sensitivity	89.00
16k > Object Detection > Moving Object Detection	DVSMOTION20	GSCEventMOD	https://arxiv.org/abs/2109.14979v3	F-Measure	66.93
16k > Object Detection > 3D Object Detection From Monocular Images	nuScenes Cars	MonoDIS	https://arxiv.org/abs/1905.12365v1	AP 2.0m	69.0
16k > Object Detection > 3D Object Detection From Monocular Images	nuScenes Cars	MonoDIS	https://arxiv.org/abs/1905.12365v1	AP 0.5m	10.7
16k > Object Detection > 3D Object Detection From Monocular Images	nuScenes Cars	MonoDIS	https://arxiv.org/abs/1905.12365v1	AP 1.0m	37.5
16k > Object Detection > 3D Object Detection From Monocular Images	nuScenes Cars	MonoDIS	https://arxiv.org/abs/1905.12365v1	AP 4.0m	85.7
16k > Object Detection > 3D Object Detection From Monocular Images	nuScenes Cars	MonoDIS	https://arxiv.org/abs/1905.12365v1	ATE	0.61
16k > Object Detection > 3D Object Detection From Monocular Images	nuScenes Cars	MonoDIS	https://arxiv.org/abs/1905.12365v1	ASE	0.15
16k > Object Detection > 3D Object Detection From Monocular Images	nuScenes Cars	MonoDIS	https://arxiv.org/abs/1905.12365v1	AOE	0.08
16k > Object Detection > 3D Object Detection From Monocular Images	Waymo Open Dataset	DEVIANT	https://arxiv.org/abs/2207.10758v1	3D mAPH Vehicle (Front Camera Only)	2.52
16k > Object Detection > 3D Object Detection From Monocular Images	Waymo Open Dataset	GUP Net	https://arxiv.org/abs/2107.13774v2	3D mAPH Vehicle (Front Camera Only)	2.14
16k > Object Detection > 3D Object Detection From Monocular Images	Waymo Open Dataset	M3D-RPN	https://arxiv.org/abs/1907.06038v2	3D mAPH Vehicle (Front Camera Only)	0.65
16k > Object Detection > 3D Object Detection From Monocular Images	KITTI-360	SeaBird + PanopticBEV	https://arxiv.org/abs/2403.20318v1	AP50	4.64
16k > Object Detection > 3D Object Detection From Monocular Images	KITTI-360	SeaBird + PanopticBEV	https://arxiv.org/abs/2403.20318v1	AP25	37.12
16k > Object Detection > 3D Object Detection From Monocular Images	KITTI-360	BoxNet	https://arxiv.org/abs/1904.09664v2	AP50	4.08
16k > Object Detection > 3D Object Detection From Monocular Images	KITTI-360	BoxNet	https://arxiv.org/abs/1904.09664v2	AP25	23.59
16k > Object Detection > 3D Object Detection From Monocular Images	KITTI-360	VoteNet	https://arxiv.org/abs/1904.09664v2	AP50	3.40
16k > Object Detection > 3D Object Detection From Monocular Images	KITTI-360	VoteNet	https://arxiv.org/abs/1904.09664v2	AP25	30.61
16k > Object Detection > 3D Object Detection From Monocular Images	KITTI-360	SeaBird + Image2Maps	https://arxiv.org/abs/2403.20318v1	AP50	3.14
16k > Object Detection > 3D Object Detection From Monocular Images	KITTI-360	SeaBird + Image2Maps	https://arxiv.org/abs/2403.20318v1	AP25	35.04
16k > Object Detection > 3D Object Detection From Monocular Images	KITTI-360	MonoDTR	https://arxiv.org/abs/2203.10981v2	AP50	3.02
16k > Object Detection > 3D Object Detection From Monocular Images	KITTI-360	MonoDTR	https://arxiv.org/abs/2203.10981v2	AP25	39.76
16k > Object Detection > 3D Object Detection From Monocular Images	KITTI-360	DEVIANT	https://arxiv.org/abs/2207.10758v1	AP50	0.88
16k > Object Detection > 3D Object Detection From Monocular Images	KITTI-360	DEVIANT	https://arxiv.org/abs/2207.10758v1	AP25	26.96
16k > Object Detection > 3D Object Detection From Monocular Images	KITTI-360	GUPNet	https://arxiv.org/abs/2107.13774v2	AP50	0.87
16k > Object Detection > 3D Object Detection From Monocular Images	KITTI-360	GUPNet	https://arxiv.org/abs/2107.13774v2	AP25	27.25
16k > Object Detection > 3D Object Detection From Monocular Images	KITTI-360	MonoDLE	https://arxiv.org/abs/2103.16237v1	AP50	0.85
16k > Object Detection > 3D Object Detection From Monocular Images	KITTI-360	MonoDLE	https://arxiv.org/abs/2103.16237v1	AP25	28.99
16k > Object Detection > 3D Object Detection From Monocular Images	KITTI-360	Cube R-CNN	https://arxiv.org/abs/2207.10660v2	AP50	0.80
16k > Object Detection > 3D Object Detection From Monocular Images	KITTI-360	Cube R-CNN	https://arxiv.org/abs/2207.10660v2	AP25	15.57
16k > Object Detection > 3D Object Detection From Monocular Images	KITTI-360	MonoDETR	https://arxiv.org/abs/2203.13310v5	AP50	0.79

16k > Object Detection > Open World Object Detection

COCO-OOD

unsniffer

https://arxiv.org/abs/2303.13769v3

unknown F1 score

0.479

16k > Object Detection > Open World Object Detection

COCO VOC to non-VOC

GOOD

https://arxiv.org/abs/2212.11720v3

AR100

39.7

16k > Object Detection > Open World Object Detection

COCO VOC to non-VOC

OLN-Box

https://arxiv.org/abs/2108.06753v1

AR100

33.4

16k > Object Detection > Open World Object Detection

PASCAL VOC 2007

ORE (MDef-DETR)

https://arxiv.org/abs/2111.11430v6

WI

0.0474

16k > Object Detection > Open World Object Detection

PASCAL VOC 2007

ORE (MDef-DETR)

https://arxiv.org/abs/2111.11430v6

A-OSE

7322

16k > Object Detection > Open World Object Detection

PASCAL VOC 2007

ORE (MDef-DETR)

https://arxiv.org/abs/2111.11430v6

MAP

64.03

16k > Object Detection > Open World Object Detection

PASCAL VOC 2007

ORE (MDef-DETR)

https://arxiv.org/abs/2111.11430v6

Unknown Recall

50.13

16k > Object Detection > Open World Object Detection

PASCAL VOC 2007

ORE

https://arxiv.org/abs/2103.02603v2

WI

0.02193

16k > Object Detection > Open World Object Detection

PASCAL VOC 2007

ORE

https://arxiv.org/abs/2103.02603v2

A-OSE

8234

16k > Object Detection > Open World Object Detection

PASCAL VOC 2007

ORE

https://arxiv.org/abs/2103.02603v2

MAP

56.34

16k > Object Detection > Open World Object Detection

PASCAL VOC 2007

ORE

https://arxiv.org/abs/2103.02603v2

Unknown Recall

14.40

16k > Object Detection > Medical Object Detection

DeepLesion

P3D

https://arxiv.org/abs/2201.01426v1

Sensitivity

88.55

16k > Object Detection > Medical Object Detection

DeepLesion

DKMA-ULD

https://arxiv.org/abs/2203.06886v1

Sensitivity

87.16

16k > Object Detection > Medical Object Detection

DeepLesion

AlignShift

https://arxiv.org/abs/2103.12277v1

Sensitivity

86.83

16k > Object Detection > Medical Object Detection

DeepLesion

MP3D

https://arxiv.org/abs/2012.08770v1

Sensitivity

86.74

16k > Object Detection > Medical Object Detection

DeepLesion

MELD

https://arxiv.org/abs/2005.13753v1

Sensitivity

86.6

16k > Object Detection > Medical Object Detection

DeepLesion

FCOS

https://arxiv.org/abs/2203.16074v1

Sensitivity

86.05

16k > Object Detection > Medical Object Detection

DeepLesion

MULAN

https://arxiv.org/abs/1908.04373v1

Sensitivity

85.22

16k > Object Detection > Medical Object Detection

DeepLesion

MVP Net

https://arxiv.org/abs/1909.04247v3

Sensitivity

83.64

16k > Object Detection > Medical Object Detection

DeepLesion

Improved RetinaNet

https://arxiv.org/abs/1906.02283v1

Sensitivity

82.36

16k > Object Detection > Medical Object Detection

DeepLesion

3DCE

http://arxiv.org/abs/1806.09648v2

Sensitivity

75.55

16k > Object Detection > Medical Object Detection

GRAZPEDWRI-DX

YOLOv8x

https://arxiv.org/abs/2407.12597v2

mAP

77.00

16k > Object Detection > Medical Object Detection

MoNuSeg 2018

CircleNet

https://arxiv.org/abs/2110.12093v1

Average-mAP

0.487

16k > Object Detection > Medical Object Detection

Barrett’s Esophagus

Attention-based model

https://arxiv.org/abs/1811.08513v2

Mean Accuracy

81%

16k > Object Detection > Medical Object Detection

Barrett’s Esophagus

Sliding Window

http://arxiv.org/abs/1703.02442v2

Mean Accuracy

74%

16k > Object Detection > Dense Object Detection

SKU-110K

RetailDet

https://arxiv.org/abs/2204.00298v4

AP

59.0

16k > Object Detection > Dense Object Detection

SKU-110K

Cascade-RCNN

https://arxiv.org/abs/2007.11946v3

AP

58.7

16k > Object Detection > Dense Object Detection

SKU-110K

SAPD

https://arxiv.org/abs/1911.12448v2

AP

55.7

16k > Object Detection > Dense Object Detection

SKU-110K

Soft-IoU + EM-Merger unit

http://arxiv.org/abs/1904.00853v3

AP

49.2

16k > Object Detection > Dense Object Detection

SKU-110K

RetinaNet

http://arxiv.org/abs/1708.02002v2

AP

45.5

16k > Object Detection > Dense Object Detection

SKU-110K

RetinaNet

http://arxiv.org/abs/1708.02002v2

AP75

.389

16k > Object Detection > Object Proposal Generation

PASCAL VOC 2012, 60 proposals per image

MDef-DETR

https://arxiv.org/abs/2111.11430v6

Average Recall

0.9126

16k > Object Detection > Object Proposal Generation

PASCAL VOC 2012, 60 proposals per image

Recurrent Pixel Embedding

http://arxiv.org/abs/1712.08273v1

Average Recall

0.814

16k > Object Detection > Object Proposal Generation

PASCAL VOC 2012, 60 proposals per image

inst-DML

http://arxiv.org/abs/1703.10277v1

Average Recall

0.667

16k > Object Detection > Object Proposal Generation

COCO (Common Objects in Context)

MDef-DETR (Off-the-shelf evaluation)

https://arxiv.org/abs/2111.11430v6

Average Recall

0.6503

16k > Object Detection > Head Detection

Rebar Head

WSMA-Seg (stack=2 ,base=40, depth=5)

https://arxiv.org/abs/1904.13300v3

F1

98.83%

16k > Object Detection > License Plate Detection

Common Voice Estonian

porshe

https://arxiv.org/abs/2206.09379v2

0S

big car