Dialogue on Visual Dialog v1.0 test-std

Metric: MRR (x 100) (higher is better)

LeaderboardDataset

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Results

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#	Model↕	MRR (x 100)▼	Extra Data	Paper	Date↕	Code
1	MRR ensemble (Naive)	71.24	No	-	-	-
2	Ensemble FGA + BERT	70.95	No	-	-	-
3	Two-Step(refactor)	70.41	No	-	-	-
4	2 Step: Factor Graph Attention + VD-Bert	69.92	No	Ensemble of MRR and NDCG models for Visual Dialog	2021-04-15	Code
5	5xFGA (F-RCNNx101)	69.3	No	Factor Graph Attention	2019-04-11	Code
6	CAF	68.16	No	-	-	-
7	w/ VQA + CC, single model	67.5	No	-	-	-
8	test1	67.5	No	-	-	-
9	sh101	67.49	No	-	-	-
10	SCL_48	66.63	No	-	-	-
11	Transformer+2cons	66.53	No	-	-	-
12	single model	66.2	No	-	-	-
13	Bert2constraints	65.7	No	-	-	-
14	single-model	64.95	No	-	-	-
15	MVAN	64.84	No	Multi-View Attention Network for Visual Dialog	2020-04-29	Code
16	jiuyigedian	64.79	No	-	-	-
17	CARE(Single Model)	64.62	No	-	-	-
18	gr	64.58	No	-	-	-
19	clean_wac_4freeze	64.57	No	-	-	-
20	disc	64.43	No	-	-	-
21	zxcdd	64.31	No	-	-	-
22	zuizhong	64.3	No	-	-	-
23	1	64.25	No	-	-	-
24	HACAN	64.22	No	Making History Matter: History-Advantage Sequenc...	2019-02-25	-
25	211	64.14	No	-	-	-
26	Bert(two-stream)	63.92	No	-	-	-
27	lijunlin_7	63.7	No	-	-	-
28	CAG	63.49	No	Iterative Context-Aware Graph Inference for Visu...	2020-04-05	Code
29	lijunlin_9	63.31	No	-	-	-
30	ERIC666	63.3	No	-	-	-
31	DualVD	63.23	No	DualVD: An Adaptive Dual Encoding Model for Deep...	2019-11-17	Code
32	DAN	63.2	No	Dual Attention Networks for Visual Reference Res...	2019-02-25	Code
33	RVA	63.03	No	Recursive Visual Attention in Visual Dialog	2018-12-06	Code
34	kbgn_disc_5	62.68	No	-	-	-
35	bert-double-stream-finetuning	62.65	No	-	-	-
36	lkh(single-model)	62.65	No	-	-	-
37	single-model	62.56	No	-	-	-
38	eightepoch	62.24	No	-	-	-
39	Synergistic	62.2	No	Image-Question-Answer Synergistic Network for Vi...	2019-02-26	-
40	wqedasd(single model)	61.87	No	-	-	-
41	CorefNMN (ResNet-152)	61.5	No	Visual Coreference Resolution in Visual Dialog u...	2018-09-06	Code
42	GNN	61.37	No	Reasoning Visual Dialogs with Structural and Par...	2019-04-11	Code
43	DLC-4	61.09	No	-	-	-
44	adasd	60.11	No	-	-	-
45	jkl	59.96	No	-	-	-
46	NMN	58.8	No	Learning to Reason: End-to-End Module Networks f...	2017-04-18	Code
47	sdfsdaf	58.57	No	-	-	-
48	shanshandu	57.19	No	-	-	-
49	1	57.13	No	-	-	-
50	1	56.73	No	-	-	-
51	1	56.67	No	-	-	-
52	ensemble, finetune	56.42	No	-	-	-
53	Ensemble + Fine-tuning	56.35	No	-	-	-
54	1	56.34	No	-	-	-
55	P1P2+Distill+Ensemble	56.2	No	-	-	-
56	VD-PCR	56.05	No	-	-	-
57	7	56.03	No	-	-	-
58	gat_disc_relto_4	55.69	No	-	-	-
59	MN-QIH-D	55.5	No	Visual Dialog	2016-11-26	Code
60	MN-QIH-D	55.4	No	Visual Dialog	2016-11-26	Code
61	Disc, Dense, 4 Ensemble.	55.11	No	-	-	-
62	HRE-QIH-D	54.2	No	Visual Dialog	2016-11-26	Code
63	paratraining1epoch	53.3	No	-	-	-
64	gat_disc_3	53.19	No	-	-	-
65	Ensemble + Finetune	52.14	No	Efficient Attention Mechanism for Visual Dialog ...	2019-11-26	Code
66	Ensemble	51.17	No	-	-	-
67	CE-finetuned, single model	50.74	No	-	-	-
68	10	49.47	No	-	-	-
69	2	49.26	No	-	-	-
70	5-2	49.03	No	-	-	-
71	5_4	48.37	No	-	-	-
72	20	47.54	No	-	-	-
73	mvan_len40_test	47.03	No	-	-	-
74	trainval_ch_9	45.84	No	-	-	-
75	Single	45.75	No	-	-	-
76	2	43.07	No	-	-	-
77	simple_test	41.66	No	-	-	-
78	5TS	39.61	No	-	-	-
79	czczx	29.97	No	-	-	-
80	qqhe	7.25	No	-	-	-

#1MRR ensemble (Naive)
71.24
MRR (x 100)
No paper
#2Ensemble FGA + BERT
70.95
MRR (x 100)
No paper
#3Two-Step(refactor)
70.41
MRR (x 100)
No paper
#42 Step: Factor Graph Attention + VD-BertSOTA
69.92
MRR (x 100)· 2021-04-15
Ensemble of MRR and NDCG models for Visual Dialog Code
#55xFGA (F-RCNNx101)SOTA
69.3
MRR (x 100)· 2019-04-11
Factor Graph Attention Code
#6CAF
68.16
MRR (x 100)
No paper
#7w/ VQA + CC, single model
67.5
MRR (x 100)
No paper
#8test1
67.5
MRR (x 100)
No paper
#9sh101
67.49
MRR (x 100)
No paper
#10SCL_48
66.63
MRR (x 100)
No paper
#11Transformer+2cons
66.53
MRR (x 100)
No paper
#12single model
66.2
MRR (x 100)
No paper
#13Bert2constraints
65.7
MRR (x 100)
No paper
#14single-model
64.95
MRR (x 100)
No paper
#15MVAN
64.84
MRR (x 100)· 2020-04-29
Multi-View Attention Network for Visual Dialog Code
#16jiuyigedian
64.79
MRR (x 100)
No paper
#17CARE(Single Model)
64.62
MRR (x 100)
No paper
#18gr
64.58
MRR (x 100)
No paper
#19clean_wac_4freeze
64.57
MRR (x 100)
No paper
#20disc
64.43
MRR (x 100)
No paper
#21zxcdd
64.31
MRR (x 100)
No paper
#22zuizhong
64.3
MRR (x 100)
No paper
#231
64.25
MRR (x 100)
No paper
#24HACANSOTA
64.22
MRR (x 100)· 2019-02-25
Making History Matter: History-Advantage Sequence Training for Visual Dialog
#25211
64.14
MRR (x 100)
No paper
#26Bert(two-stream)
63.92
MRR (x 100)
No paper
#27lijunlin_7
63.7
MRR (x 100)
No paper
#28CAG
63.49
MRR (x 100)· 2020-04-05
Iterative Context-Aware Graph Inference for Visual Dialog Code
#29lijunlin_9
63.31
MRR (x 100)
No paper
#30ERIC666
63.3
MRR (x 100)
No paper
#31DualVD
63.23
MRR (x 100)· 2019-11-17
DualVD: An Adaptive Dual Encoding Model for Deep Visual Understanding in Visual Dialogue Code
#32DAN
63.2
MRR (x 100)· 2019-02-25
Dual Attention Networks for Visual Reference Resolution in Visual Dialog Code
#33RVASOTA
63.03
MRR (x 100)· 2018-12-06
Recursive Visual Attention in Visual Dialog Code
#34kbgn_disc_5
62.68
MRR (x 100)
No paper
#35bert-double-stream-finetuning
62.65
MRR (x 100)
No paper
#36lkh(single-model)
62.65
MRR (x 100)
No paper
#37single-model
62.56
MRR (x 100)
No paper
#38eightepoch
62.24
MRR (x 100)
No paper
#39Synergistic
62.2
MRR (x 100)· 2019-02-26
Image-Question-Answer Synergistic Network for Visual Dialog
#40wqedasd(single model)
61.87
MRR (x 100)
No paper
#41CorefNMN (ResNet-152)SOTA
61.5
MRR (x 100)· 2018-09-06
Visual Coreference Resolution in Visual Dialog using Neural Module Networks Code
#42GNN
61.37
MRR (x 100)· 2019-04-11
Reasoning Visual Dialogs with Structural and Partial Observations Code
#43DLC-4
61.09
MRR (x 100)
No paper
#44adasd
60.11
MRR (x 100)
No paper
#45jkl
59.96
MRR (x 100)
No paper
#46NMNSOTA
58.8
MRR (x 100)· 2017-04-18
Learning to Reason: End-to-End Module Networks for Visual Question Answering Code
#47sdfsdaf
58.57
MRR (x 100)
No paper
#48shanshandu
57.19
MRR (x 100)
No paper
#491
57.13
MRR (x 100)
No paper
#501
56.73
MRR (x 100)
No paper
#511
56.67
MRR (x 100)
No paper
#52ensemble, finetune
56.42
MRR (x 100)
No paper
#53Ensemble + Fine-tuning
56.35
MRR (x 100)
No paper
#541
56.34
MRR (x 100)
No paper
#55P1P2+Distill+Ensemble
56.2
MRR (x 100)
No paper
#56VD-PCR
56.05
MRR (x 100)
No paper
#577
56.03
MRR (x 100)
No paper
#58gat_disc_relto_4
55.69
MRR (x 100)
No paper
#59MN-QIH-DSOTA
55.5
MRR (x 100)· 2016-11-26
Visual Dialog Code
#60MN-QIH-D
55.4
MRR (x 100)· 2016-11-26
Visual Dialog Code
#61Disc, Dense, 4 Ensemble.
55.11
MRR (x 100)
No paper
#62HRE-QIH-D
54.2
MRR (x 100)· 2016-11-26
Visual Dialog Code
#63paratraining1epoch
53.3
MRR (x 100)
No paper
#64gat_disc_3
53.19
MRR (x 100)
No paper
#65Ensemble + Finetune
52.14
MRR (x 100)· 2019-11-26
Efficient Attention Mechanism for Visual Dialog that can Handle All the Interactions between Multiple Inputs Code
#66Ensemble
51.17
MRR (x 100)
No paper
#67CE-finetuned, single model
50.74
MRR (x 100)
No paper
#6810
49.47
MRR (x 100)
No paper
#692
49.26
MRR (x 100)
No paper
#705-2
49.03
MRR (x 100)
No paper
#715_4
48.37
MRR (x 100)
No paper
#7220
47.54
MRR (x 100)
No paper
#73mvan_len40_test
47.03
MRR (x 100)
No paper
#74trainval_ch_9
45.84
MRR (x 100)
No paper
#75Single
45.75
MRR (x 100)
No paper
#762
43.07
MRR (x 100)
No paper
#77simple_test
41.66
MRR (x 100)
No paper
#785TS
39.61
MRR (x 100)
No paper
#79czczx
29.97
MRR (x 100)
No paper
#80qqhe
7.25
MRR (x 100)
No paper