dct_matrix = np.zeros(shape=(28, 28, 64)) for i in range(0, img_perchannel.shape[0], 8): for j in range(0, img_perchannel.shape[1], 8): dct[i:(i + 8), j:(j + 8)] = np.log(np.abs(cv2.dct(img_perchannel[i:(i + 8), j:(j + 8)]))) dct_matrix[i // 8...
论文:Learning in the Frequency Domain, CVPR 2020 代码:github.com/calmevtime/D 实际的图像尺寸比较大,无法直接输入到CNN处理。因此,各类CNN模型都把图像首先下采样的224x224,然后再处理。但是,这样会引起信息损失并影响准确率。因此,阿里巴巴的研究人员提出新的方法,把RGB图像变换到DCT频率域,而不是直接下采样。
Learning in the Frequency Domain 解读 论文:Learning in the Frequency Domain, CVPR 2020 代码:https://github.com/calmevtime/DCTNet 实际的图像尺寸比较大,无法直接输入到CNN处理。因此,各类CNN模型都把图像首先下采样的224x224,然后再处理。但是,这样会引起信息损失并影响准确率。因此,阿里巴巴的研究人员提出新...
4、静态频率通道选择 笔者并不是特别明白为什么这一部分被称之为Static Frequency Channel Selection,因为这一部分更多的是描述一些实验性的结果。 图五展示了两个输入频道的热图可视化,(a)描述的是基于ImageNet的图像分类,(b)描述的是基于coco数据集的实例分割。基于图五,文章描述了几个发现: a)相较于高频通道,低...
论文题目:《Learning in the Frequency Domain》 论文地址:https://arxiv.org/pdf/2002.12416.pdf 论文翻译参考: CVPR2020:Learning in the Frequency Domain(翻译)(一) CVPR2020:Learning in the Frequency Domain(翻译)(二) 论文阅读参考: CVPR2020- 频域学习一半的数据输入,提升MASK RCNN | Learning in the ...
The official repository for NeurIPS'24 paper "Continual Learning in the Frequency Domain". We extended the original repo DER++ with our method.SetupUse argument --load_best_args to use the best hyperparameters from the paper. New models can be added to the models/ folder. New datasets can ...
将CNN的输入由RGB 3通道变成192个频域通道,结果会如何?阿里达摩院新出的paper《Learning in the Frequency Domain》实践了这个idea,并且在图像分类、实例分割任务上取得不错的表现。 Specifically for ImageNet clas- sification with the same input size, the proposed method achieves 1.41% and 0.66% top-1 accu...
Learning in the Frequency Domain 下载积分: 1000 内容提示: Learning in the Frequency DomainKai Xu 1,2∗ Minghai Qin 1 Fei Sun 1Yuhao Wang 1 Yen-kuang Chen 1 Fengbo Ren 21 DAMO Academy, Alibaba Group 2 Arizona State UniversityAbstractDeep neural networks have achieved remarkable suc-cess in...
几篇论文实现代码:《Jointly Learning Explainable Rules for Recommendation with Knowledge Graph》(WWW 2019) GitHub: O网页链接《Hierarchical Shot Detector》 (ICCV2019) GitHub:O网页链接《MelNet: A Generative Model for Audio in the Frequency Domain》(2019) GitHub: O网页链接...
Inspired by HVS, we propose a novel framework called Continual Learning in the Frequency Domain (CLFD). To our knowledge, this is the first study to utilize frequency domain features to enhance the performance and efficiency of CL training on edge devices. For the input features of the ...