Visual Dialog On Visdial V09 Val

Metrics

MRR

Mean Rank

R@1

R@10

R@5

Results

Performance results of various models on this benchmark

						Paper Title
HieCoAtt-QI	57.88	5.84	43.51	83.96	74.49	Hierarchical Question-Image Co-Attention for Visual Question Answering
HRE-QIH-D	0.5807	5.78	43.82	84.07	74.68	Visual Dialog
HRE-QIH-D	0.5846	5.72	44.67	84.22	74.50	Visual Dialog
MN-QIH-D	0.5965	5.46	45.55	85.37	76.22	Visual Dialog
AMEM	-	4.86	48.53	87.43	78.66	Visual Reference Resolution using Attention Memory for Visual Dialog
HCIAE-NP-ATT	62.22	4.81	48.48	87.59	78.75	Best of Both Worlds: Transferring Knowledge from Discriminative Learning to a Generative Visual Dialog Model
SF-QIH-se-2	62.42	4.70	48.55	87.75	78.96	Two can play this Game: Visual Dialog with Discriminative Question Generation and Answering
GNN	0.6285	4.57	48.95	88.36	79.65	Reasoning Visual Dialogs with Structural and Partial Observations
CorefNMN	63.6	4.53	50.24	88.51	79.81	Visual Coreference Resolution in Visual Dialog using Neural Module Networks
CoAtt	63.98	4.47	50.29	88.81	80.71	Are You Talking to Me? Reasoned Visual Dialog Generation through Adversarial Learning
CorefNMN (ResNet-152)	64.1	4.45	50.92	88.81	80.18	Visual Coreference Resolution in Visual Dialog using Neural Module Networks
DualVD	62.94	4.17	48.64	89.94	80.89	DualVD: An Adaptive Dual Encoding Model for Deep Visual Understanding in Visual Dialogue
DAN	66.38	4.04	53.33	90.38	82.42	Dual Attention Networks for Visual Reference Resolution in Visual Dialog
HACAN	0.6792	3.97	54.76	90.68	83.03	Making History Matter: History-Advantage Sequence Training for Visual Dialog
RVA	0.6634	3.93	52.71	90.73	82.97	Recursive Visual Attention in Visual Dialog
CAG	0.6756	3.75	54.64	91.48	83.72	Iterative Context-Aware Graph Inference for Visual Dialog
MVAN	0.6765	3.73	54.65	91.47	83.85	Multi-View Attention Network for Visual Dialog
9xFGA (VGG)	68.92	3.39	55.16	92.95	86.26	Factor Graph Attention

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Visual Dialog On Visdial V09 Val

Metrics

MRR

Mean Rank

R@1

R@10

R@5

Results

Performance results of various models on this benchmark

						Paper Title
HieCoAtt-QI	57.88	5.84	43.51	83.96	74.49	Hierarchical Question-Image Co-Attention for Visual Question Answering
HRE-QIH-D	0.5807	5.78	43.82	84.07	74.68	Visual Dialog
HRE-QIH-D	0.5846	5.72	44.67	84.22	74.50	Visual Dialog
MN-QIH-D	0.5965	5.46	45.55	85.37	76.22	Visual Dialog
AMEM	-	4.86	48.53	87.43	78.66	Visual Reference Resolution using Attention Memory for Visual Dialog
HCIAE-NP-ATT	62.22	4.81	48.48	87.59	78.75	Best of Both Worlds: Transferring Knowledge from Discriminative Learning to a Generative Visual Dialog Model
SF-QIH-se-2	62.42	4.70	48.55	87.75	78.96	Two can play this Game: Visual Dialog with Discriminative Question Generation and Answering
GNN	0.6285	4.57	48.95	88.36	79.65	Reasoning Visual Dialogs with Structural and Partial Observations
CorefNMN	63.6	4.53	50.24	88.51	79.81	Visual Coreference Resolution in Visual Dialog using Neural Module Networks
CoAtt	63.98	4.47	50.29	88.81	80.71	Are You Talking to Me? Reasoned Visual Dialog Generation through Adversarial Learning
CorefNMN (ResNet-152)	64.1	4.45	50.92	88.81	80.18	Visual Coreference Resolution in Visual Dialog using Neural Module Networks
DualVD	62.94	4.17	48.64	89.94	80.89	DualVD: An Adaptive Dual Encoding Model for Deep Visual Understanding in Visual Dialogue
DAN	66.38	4.04	53.33	90.38	82.42	Dual Attention Networks for Visual Reference Resolution in Visual Dialog
HACAN	0.6792	3.97	54.76	90.68	83.03	Making History Matter: History-Advantage Sequence Training for Visual Dialog
RVA	0.6634	3.93	52.71	90.73	82.97	Recursive Visual Attention in Visual Dialog
CAG	0.6756	3.75	54.64	91.48	83.72	Iterative Context-Aware Graph Inference for Visual Dialog
MVAN	0.6765	3.73	54.65	91.47	83.85	Multi-View Attention Network for Visual Dialog
9xFGA (VGG)	68.92	3.39	55.16	92.95	86.26	Factor Graph Attention

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