Less distraction, more machine learning action

Опубликовано 31 января 2024, 15:02

E2E learned compression may take the lead in image coding for machines, but its insufficient flexibility in adaptively allocating bits can sacrifice machine vision performance. Leveraging Regions-of-Interest can minimize the bits allocated for backgrounds, resulting in reduced bitrates while retaining the accuracy of machine tasks. Learn more about how this method can achieve impressive gains within learned image codecs.

Ready to find out more? Read the whitepaper by Jukka I. Ahonen, Nam Le, Honglei Zhang, Francesco Cricri and Esa Rahtu.
ieeexplore.ieee.org/document/1...