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, …
While most prior works focus on indoor scenes, we are one of the first to propose a label-efficient semantic segmentation pipeline for outdoor scenes with LiDAR point clouds. Our method co-designs an efficient labeling process with semi/weakly supervised learning and is applicable to nearly any ...
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 ...
Collecting labeled data for the task of semantic segmentation is expensive and time-consuming, as it requires dense pixel-level annotations. While recent Convolutional Neural Network (CNN) based semantic segmentation approaches have achieved impressive results by using large amounts of labeled training da...
Abstract.The crux of semi-supervised semantic segmentation is to assign adequate pseudo-labels to the pixels of unlabeled images. A common practice is to select the highly confident predictions as the pseudo ground-truth, but it leads to a problem that most pixels may be left unused due to th...
此外,我们引入了四个特定任务的损失函数和两阶段训练过程,以实现稳定的多模态学习。我们的方法在nuScenes数据集上显著超越了最先进的方法。此外,在不同3D骨干网络以及Waymo和Semantickitti数据集上的实验结果也显示了我们方法的可扩展性和轻量级特征。 未来工作。未来有一些工作需要改进和解决。我们提出的框架目前仅在室外...
3D semantic segmentation is the task of assigning semantic labels to each point in a 3D point cloud. Point-wise categorical annotations are collected as ground truth for this task. IoU (Intersection over Union) and mean IoU (mIoU) are commonly used metrics for evaluations. IoU measures the ove...
ing a two-fold approach to address the collapse problem: 1) self-supervised source pretraining to learn task-independent features leading to better transfer; and 2) using the language modality to ground the self-supervised representations to an independent semantic space: during pretraini...
在CVCEndoSceneStill和AS-OCT数据集上进行的大量实验和分析表明,当只给出少量强注释实例时,我们的框架能够从大量弱注释实例中学习,并获得与相应的完全监督版本接近的性能。 相关性工作 Weakly Supervised Semantic Segmentation. 弱监督语义分割旨在通过利用低成本标签来减少注释工作(Lin et al 2016;Dai, He, Sun 2015...