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

Reidentify people in new scenes better by using multiple networks

Reidentify people in new scenes better by using multiple networks


Learning to Disentangle Scenes for Person Re-identification



There are many challenging problems in the person re-identification (ReID) task, such as the occlusion and scale variation.


... usually tried to solve them by employing ... one-branch network needs to be robust to various challenging problems, which makes this network overburdened.


... proposes ... employ several self-supervision operations to simulate different challenging problems and handle each challenging problem using different networks.


... use the random erasing operation and propose a novel random scaling operation to generate new images with controllable characteristics.


A general multi-branch network ... introduced to handle different scenes ... In this way ... are effectively disentangled ...


... method achieves state-of-the-art performances on three ReID benchmarks and two occluded ReID benchmarks. ...



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


47 views0 comments

Comments


ClickBank paid link

bottom of page