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

Better detection of multiple objects when only using image-level labels with WSCL

Better detection of multiple objects when only using image-level labels with WSCL


Object Discovery via Contrastive Learning for Weakly Supervised Object Detection



Weakly Supervised Object Detection (WSOD) is a task that detects objects in an image using a model trained only on image-level annotations.


... since weak supervision does not include count or location information, the most common ``argmax'' labeling method often ignores many instances of objects.


... propose a novel multiple instance labeling method called object discovery.


... introduce a new contrastive loss under weak supervision where no instance-level information is available for sampling, called weakly supervised contrastive loss (WSCL).


WSCL aims to construct a credible similarity threshold for object discovery by leveraging consistent features for embedding vectors in the same class.


... achieve new state-of-the-art results on MS-COCO 2014 and 2017 as well as PASCAL VOC 2012, and competitive results on PASCAL VOC 2007.



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



74 views0 comments

Comments


ClickBank paid link

bottom of page