在本文中作者称之为“Few shot semantic segmentation methods”,并用DDPM的生成器替换了StyleGAN生成器进行了第二组实验。 所以这个大表能看出如下结论: 1)DDPM有着最好的语义分割结果;MAE紧随其后; 2)SwAV性能不佳:用判别式的方法进行预训练会压缩细粒度的语义信息(SwAV是对同一张图的不同视角进行判断) 3)...
@article{baranchuk2021label, title={Label-efficient semantic segmentation with diffusion models}, author={Baranchuk, Dmitry and Rubachev, Ivan and Voynov, Andrey and Khrulkov, Valentin and Babenko, …
Semantic segmentation of LiDAR point clouds is an important task in autonomous driving. However, training deep models via conventional supervised methods requires large datasets which are costly to label. It is critical to have label-efficient segmentation approaches to scale up the model to new ...
Official implementation of the paper Label-Efficient Semantic Segmentation with Diffusion ModelsThis code is based on datasetGAN and guided-diffusion.Note: use --recurse-submodules when clone.OverviewThe paper investigates the representations learned by the state-of-the-art DDPMs and shows that they ...
Contrastive Learning for Label Efficient Semantic Segmentation X Zhao,R Vemulapalli,PA Mansfield,... - International Conference on Computer Vision 被引量: 0发表: 2021年 SiamSeg: Self-Training with Contrastive Learning for Unsupervised Domain Adaptation Semantic Segmentation in Remote Sensing Semantic ...
[CVPR'22 & IJCV'24] Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels & Using Unreliable Pseudo-Labels for Label-Efficient Semantic Segmentation - Haochen-Wang409/U2PL
This paper presents the first comprehensive survey of label-efficient learning of point clouds. We address three critical questions in this emerging research field: i) the importance and urgency of label-efficient learning in point cloud processing, ii) the subfields it encompasses, and iii) the ...
Selecting a tool with these features ensures your workflow remains efficient and adaptable, no matter the size or complexity of your project. Selecting the Right Image Annotation Tool Labeler working on an image annotation task This depends on your project’s specific requirements, whether it’s for...
The Auto-Label service of TAO Data Servcies is designed to reduce the time spent annotating an image dataset. Currently, this service supports: * automatically generating bounding box annotations given category names or referring expressions. * automatically generating instance segmentation masks given ...