PT Unknown
AU Bojana Gajic
   Ariel Amato
   Ramon Baldrich
   Carlo Gatta
TI Bag of Negatives for Siamese Architectures
BT 30th British Machine Vision Conference
PY 2019
AB Training a Siamese architecture for re-identification with a large number of identities is a challenging task due to the difficulty of finding relevant negative samples efficiently. In this work we present Bag of Negatives (BoN), a method for accelerated and improved training of Siamese networks that scales well on datasets with a very large number of identities. BoN is an efficient and loss-independent method, able to select a bag of high quality negatives, based on a novel online hashing strategy.
ER