Tasks SotA Datasets Papers Methods Submit About

Papers With Code 2

A community resource for machine learning research: papers, code, benchmarks, and state-of-the-art results.

Explore

Notable Benchmarks All SotA Datasets Papers Methods

Community

Submit Results About

Data sourced from the PWC Archive (CC-BY-SA 4.0). Built by the community, for the community.

Models/NMN

NMN

Reported on 12 benchmarks across 2 tasks · 1 paper · 10 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Speech6 results

DialogueonVisual Dialog v1.0 test-std
MRR (x 100)· 2017-04-18
58.8
best: 71.24 (MRR ensemble (Naive))
SOTA
Learning to Reason: End-to-End Module Networks for Visual Question Answering arXiv:1704.05526
DialogueonVisual Dialog v1.0 test-std
NDCG (x 100)· 2017-04-18
58.1
best: 78.7 (Single)
SOTA
Learning to Reason: End-to-End Module Networks for Visual Question Answering arXiv:1704.05526
DialogueonVisual Dialog v1.0 test-std
R@1· 2017-04-18
44.15
best: 58.3 (2 Step: Factor Graph Attention + VD-Bert)
SOTA
Learning to Reason: End-to-End Module Networks for Visual Question Answering arXiv:1704.05526
DialogueonVisual Dialog v1.0 test-std
R@10· 2017-04-18
86.88
best: 95.08 (Ensemble FGA + BERT)
SOTA
Learning to Reason: End-to-End Module Networks for Visual Question Answering arXiv:1704.05526
DialogueonVisual Dialog v1.0 test-std
R@5· 2017-04-18
76.88
best: 88.42 (Ensemble FGA + BERT)
SOTA
Learning to Reason: End-to-End Module Networks for Visual Question Answering arXiv:1704.05526
DialogueonVisual Dialog v1.0 test-std
Mean· 2017-04-18
4.4
best: 49.61 (qqhe)
Learning to Reason: End-to-End Module Networks for Visual Question Answering arXiv:1704.05526

Computer Vision6 results

Visual DialogonVisual Dialog v1.0 test-std
MRR (x 100)· 2017-04-18
58.8
best: 71.24 (MRR ensemble (Naive))
SOTA
Learning to Reason: End-to-End Module Networks for Visual Question Answering arXiv:1704.05526
Visual DialogonVisual Dialog v1.0 test-std
NDCG (x 100)· 2017-04-18
58.1
best: 78.7 (Single)
SOTA
Learning to Reason: End-to-End Module Networks for Visual Question Answering arXiv:1704.05526
Visual DialogonVisual Dialog v1.0 test-std
R@1· 2017-04-18
44.15
best: 58.3 (2 Step: Factor Graph Attention + VD-Bert)
SOTA
Learning to Reason: End-to-End Module Networks for Visual Question Answering arXiv:1704.05526
Visual DialogonVisual Dialog v1.0 test-std
R@10· 2017-04-18
86.88
best: 95.08 (Ensemble FGA + BERT)
SOTA
Learning to Reason: End-to-End Module Networks for Visual Question Answering arXiv:1704.05526
Visual DialogonVisual Dialog v1.0 test-std
R@5· 2017-04-18
76.88
best: 88.42 (Ensemble FGA + BERT)
SOTA
Learning to Reason: End-to-End Module Networks for Visual Question Answering arXiv:1704.05526
Visual DialogonVisual Dialog v1.0 test-std
Mean· 2017-04-18
4.4
best: 49.61 (qqhe)
Learning to Reason: End-to-End Module Networks for Visual Question Answering arXiv:1704.05526