Factor Graph Attention

Dialog is an effective way to exchange information, but subtle details and nuances are extremely important. While significant progress has paved a path to address visual dialog with algorithms, details and nuances remain a challenge... (read more)

PDF Abstract CVPR 2019 PDF CVPR 2019 Abstract

Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Visual Dialog VisDial v0.9 val 9xFGA (VGG) MRR 68.92 # 1
Mean Rank 3.39 # 1
R@1 55.16 # 1
R@10 92.95 # 1
R@5 86.26 # 1
Visual Dialog Visual Dialog v1.0 test-std 5xFGA (F-RCNNx101) NDCG (x 100) 57.20 # 42
MRR (x 100) 69.3 # 5
R@1 55.65 # 5
R@5 86.73 # 3
R@10 94.05 # 3
Mean 3.14 # 52

Methods used in the Paper


METHOD TYPE
FGA
Attention
Interpretability
Image Models