CCA - Fast RCNN

Reported on 3 benchmarks across 1 task · 1 paper · 3 SOTA

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

Natural Language Processing3 results

Phrase GroundingonFlickr30k Entities Test
R@1· 2015-05-19
41.77
best: 87.7 (GLIPv2)
SOTA
Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models arXiv:1505.04870
Phrase GroundingonFlickr30k Entities Test
R@10· 2015-05-19
70.77
best: 98.1 (GLIP)
SOTA
Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models arXiv:1505.04870
Phrase GroundingonFlickr30k Entities Test
R@5· 2015-05-19
64.52
best: 96.9 (GLIP)
SOTA
Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models arXiv:1505.04870