top of page

News to help your R&D in artificial intelligence, machine learning, robotics, computer vision, smart hardware

As an Amazon Associate I earn

from qualifying purchases

Writer's picturemorrislee

Segment new objects without forgetting old ones by replaying most informative samples with Zhu

Segment new objects without forgetting old ones by replaying most informative samples with Zhu


Continual Semantic Segmentation with Automatic Memory Sample Selection

arXiv paper abstract https://arxiv.org/abs/2304.05015



Continual Semantic Segmentation (CSS) extends static semantic segmentation by incrementally introducing new classes for training.


To alleviate the catastrophic forgetting issue in CSS, a memory buffer that stores a small number of samples from the previous classes is constructed for replay.


However, existing methods select the memory samples either randomly or based on a single-factor-driven handcrafted strategy, which has no guarantee to be optimal.


... propose a novel memory sample selection mechanism that selects informative samples for effective replay in a fully automatic way by considering comprehensive factors including sample diversity and class performance.


... mechanism regards the selection operation as a decision-making process and learns an optimal selection policy that directly maximizes the validation performance on a reward set.


... demonstrate the effectiveness of ... approach with state-of-the-art (SOTA) performance achieved ...



Please like and share this post if you enjoyed it using the buttons at the bottom!


Stay up to date. Subscribe to my posts https://morrislee1234.wixsite.com/website/contact

Web site with my other posts by category https://morrislee1234.wixsite.com/website



72 views0 comments

Comments


ClickBank paid link

bottom of page