特征库机制本身在源数据上就很强 对更新特征的消融实验 在得到互相关图后使用 LN 的消融实验 得到权重图的池化操作消融实验 各种图的可视化结果 论文信息 Dynamic Momentum Adaptation for Zero-Shot Cross-Domain Crowd Counting visal.cs.cityu.edu.hk/s 编辑于 2021-11-26 16:08 ...
Error-Aware Density Isomorphism Reconstruction for Unsupervised Cross Domain Crowd Counting 引用
内容提示: Leveraging Self-Supervision for Cross-Domain Crowd CountingWeizhe Liu Nikita Durasov Pascal FuaComputer Vision Laboratory,´Ecole Polytechnique Fédérale de Lausanne (EPFL){weizhe.liu, nikita.durasov, pascal.fua}@epfl.chAbstractState-of-the-art methods for counting people in crowdedscenes...
README.md add implementation May 4, 2022 model.py add implementation May 4, 2022 README This repository is a PyTorch implementation for the paperLeveraging Self-Supervision for Cross-Domain Crowd Counting, which is accepted asoralpresentation at CVPR 2022. If you use this code in your research...
Due to the hidden nodes, the conditional probability of cannot be drawn simply by counting the occurrence of each condition. An EM algorithm was proposed to learn the parameters in an unsupervised manner. Example 14: Yuan et al. [74][76] infer the functional re- gions in a city using ...
domain adaptationdensity map estimationadversarial learningGiven an image, crowd counting aims to estimate the amount of target objects in the image. With un-predictable installation situations of surveillance systems (or other equipments), crowd counting images from different data sets may exhibit severe...
Recently, Cross-Domain Adaptive Crowd Counting (CDACC) has received extensive attention due to its independence from large numbers of expensive annotation samples. CDACC aims to train a counting model using the low-cost labeled data as the source domain and generalize it to the target domain. ...
来自专栏 · Crowd Counting 主要思路和创新点 经典的跨域算法通常会对源域进行处理:1. style transfer (已知目标域的风格,只使用了目标域先验); 2. Domian Randomization(不知目标域风格,增强模型跨域表达能力,没有使用目标先验)。这些转换方式不是最优的,因此作者提出了基于任务和目标风格的自动搜索转换器。具体做...
首发于Crowd Counting 切换模式写文章 登录/注册 Leveraging Self-Supervision for Cross-Domain Crowd Counting 啊耀 来自专栏 · Crowd Counting 动机和方法: 传统人群计数的方法需要大量的数据,需要繁琐的标注。看起来利用虚拟合成数据来进行网络的训练是合适的。但是虚拟数据和真实数据有着很大的domain shift。因此...
Error-aware density isomorphism reconstruction for unsupervised cross-domain crowd counting Domain structure-based transfer learning for cross-domain word representation Cross-Domain Similarity Learning for Face Recognition in Unseen Domains Face Parsing From RGB and Depth Using Cross-Domain Mutual Learning Un...