From Coarse to Fine-grained Concept based Discrimination for Phrase Detection. (arXiv:2112.03237v2 [cs.CV] UPDATED)

Phrase detection requires methods to identify if a phrase is relevant to an
image and localize it if applicable. A key challenge in training more
discriminative phrase detection models is sampling negatives. However, sampling
techniques from prior work focus primarily on hard, often noisy, negatives
disregarding the broader distribution of negative samples. To address this
problem, we introduce CFCD-Net, a phrase detector that differentiates between
phrases through two novels methods. First, we generate groups that consist of
semantically similar words …

arxiv concept detection discrimination fine-grained