既然是为了解决类与类之间的决策边界不明显的问题,那么我在分割中引入更多的显式类信息不就好了,所以作者的论文题目叫Semantic-Aware。所谓semantic,说白了就是类。semantic-aware说人话就是有较为明确的目标类信息给你支撑分割。 但是分割前,哪里来的显式类信息,答曰:伪标签 那么作者是怎么显式引入目标类信息的了。
Semantic-Aware Domain Generalized Segmentationarxiv.org/abs/2204.00822 一 文章出发点 宏观:为了解决语义分割模型的领域泛化问题。此处泛化是指不需要任何目标域数据。 微观:现有的方法不能够得到较好的类边界,也就是说,类与类之间的决策边界不明显。 二 文章核心思想 既然是为了解决类与类之间的决策边界不明显...
(2021) addressed domain generalized semantic segmentation by proposing a novel meta-learning scheme with feature disentanglement ability. Zhang et al. (2022a) developed a domain generalization framework that jointly exploits the model-agnostic training scheme and target-specific normalization test strategy ...
论文标题: Stronger, Fewer, & Superior: Harnessing Vision Foundation Models for Domain Generalized Semantic Segmentation 论文地址:https://arxiv.org/pdf/2312.04265.pdf 代码:https://github.com/w1oves/Rein.git 发表于:CVPR 2024 作者起名的一些巧思: rein 缰绳 harness 驾驭 harness vision foundation model ...
In this paper, we introduce a method to tackle Domain Generalized Semantic Segmentation (DGSS) by utilizing domain-invariant semantic knowledge from text embeddings of vision-language models. We employ the text embeddings as object queries within a transformer-based segmentation framework (textual object...
Style-Hallucinated Dual Consistency Learning for Domain Generalized Semantic Segmentationarxiv.org/abs/2204.02548 在这项工作中,我们提出了风格幻觉双一致性学习(SHADE)框架来处理这种领域转换。具体来说,SHADE是基于两个一致性约束构建的,即风格一致性(SC)和回顾一致性(RC)。此外,我们提出了一种新的风格幻觉模...
Adversarial Semantic Hallucination for Domain Generalized Semantic Segmentation,获取车牌轮廓上的点集后,可用cv2.minAreaRect()获取点集的最小外接矩形。返回值rect内包含该矩形的中心点坐标、高度宽度及倾斜角度等信息,使用cv2.boxPoints()可获取该矩形的四个顶点
{Domain Game}, to perform better feature distangling for medical image segmentation, based on the observation that diagnostic relevant features are more sensitive to geometric transformations, whilist domain-specific features probably will remain invariant to such operations. In domain game, a set of ...
Domain Generalized Semantic Segmentation (DGSS) deals with training a model on a labeled source domain with the aim of generalizing to unseen domains during inference. Existing DGSS methods typically effectuate robust features by means of Domain Randomization (DR). Such an approach is often limited ...
Semantic-Aware Domain Generalized Segmentation IEEE/CVF Computer Vision and Pattern Recognition (CVPR 2022) If you find it helpful to your research, please cite as follows: @inproceedings{peng2022semantic, title={Semantic-Aware Domain Generalized Segmentation}, author={Peng, Duo and Lei, Yinjie and...