论文:Boundary-Guided Camouflaged Object Detection 代码:github.com/thograce/BGN 问题 论文试图解决什么问题? 伪装物体的边界与背景之间的分界相当模糊并且难以区分, 不引入额外的先验信息很难精准的定位到伪装物体。并且,现有的方法往往无法分割出伪装物体的完整边界。 论文中提到的解决方案之关键是什么? 作者设计...
Boundary-guided fusion module(BFM) I_m :初始预测图 I_e :初始边缘图 I_f :输入特征 在BFM中,首先利用I_f分别生成前景特征和背景特征。 F_f = I_f ●I_m,F_b = I_f●(1-I_m) 然后,将前景特征和边界特征与边界信息融合,生成边界更清晰的特征,代码中不是简单的cat,是一种分组插片融合的方式...
Besides, a boundary-guided feature interaction module is designed to aggregate multi-level features and investigate the complementary relationship between the targets and the corresponding contours. We evaluate BCNet on four benchmark datasets to verify the effectiveness of the key modules. The ...
Boundary guided扩散模型语义控制 Boundary Guided Learning-Free Semantic Control with Diffusion Models 作者指出直接用ddim做inverted latent encoding得到的x_T,基本没办法在上面做semantic editing。而直接采样的x_T上面做semantic editing的效果却很好。 作者指出,这是因为ddim做inverted latent encoding,和直接采样x_T...
However, it still remains non-trivial to thoroughly utilize the multi-level convolutional feature maps and boundary information for salient object detection. In this paper, we propose a novel FCN framework to integrate multi-level convolutional features recurrently with the guidance of object boundary ...
After obtaining the initial location of the camouflaged regions, the corresponding boundary maps can be calculated. Second, we propose a Boundary-guided Fusion Module (BFM) to integrate features extracted from the second branch of the backbone network under the guidance of the boundary feature. ...
thograce/BGNetPublic Notifications Fork21 Star94 Boundary-Guided Camouflaged Object Detection 94stars21forksBranchesTagsActivity Star Notifications master 1Branch0Tags Code Folders and files 337501a·Nov 27, 2022 16 Commits .idea checkpoints/best ...
Explicit Boundary Guided Semi-Push-Pull Contrastive Learning for Supervised Anomaly Detection Introduction 只关注正常样本可能会限制AD模型的可判别性。如图1(a)所示,在没有异常情况的情况下,决策边界通常是隐式的,没有足够的判别性。在无监督异常检测中,由于缺乏对异常的了解,导致可判别性不足。 半监督学习利用...
作者设计了一个边缘检测模块(Boundary Detector)和一个边缘引导(Boundary Guide)模块,前者负责提取有价值的边缘先验,后者负责将边缘先验传播到分离开的前景流和背景流之中,对应利用边缘增强检测精度环节。 作者设计了一个分离注意力模块(Separated Attention module),SEA模块有两个流组成,通过reverse attention的方法使得两...
https://github.com/mahaoxiang822/Boundary-Guided-Context-Aggregation/blob/main/model/BCANet.py importtorchimporttorch.nn.functionalasFfromtorchimportnnfrommodel.dilated_resnetimportget_resnet50_baseline,get_resnet101_baselineclassBCA(nn.Module):def__init__(self,xin_channels,yin_channels,mid_channels...