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 objects with limited labels by collaboration of output and representation spaces with CSS

Segment objects with limited labels by collaboration of output and representation spaces with CSS


Space Engage: Collaborative Space Supervision for Contrastive-based Semi-Supervised Semantic Segmentation

arXiv paper abstract https://arxiv.org/abs/2307.09755



Semi-Supervised Semantic Segmentation (S4) aims to train a segmentation model with limited labeled images and a substantial volume of unlabeled images.


To improve the robustness of representations, powerful methods introduce a pixel-wise contrastive learning approach in latent space (i.e., representation space) that aggregates the representations to their prototypes in a fully supervised manner.


However, previous contrastive-based S4 methods merely rely on the supervision from the model's output (logits) in logit space during unlabeled training.


In contrast, ... utilize the outputs in both logit space and representation space to obtain supervision in a collaborative way.


The supervision from two spaces plays two roles: 1) reduces the risk of over-fitting to incorrect semantic information in logits with the help of representations; 2) enhances the knowledge exchange between the two spaces.


... demonstrate the competitive performance of ... method compared with state-of-the-art methods.



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



42 views0 comments

Comments


ClickBank paid link

bottom of page