文献阅读:Dual Contrastive Learning for General Face Forgery Detection——AAAI 2022 Echo 8 人赞同了该文章 Abstract 1. 过往方法不足:以往的研究总是将人脸伪造检测表述为基于交叉熵损失的分类问题,强调类别级差异,而不是真实和假人脸之间的本质差异,限制了模型在不可见领域的泛化。 2. 本文方法:提出了一种新...
RecDCL: Dual Contrastive Learning for Recommendationarxiv.org/pdf/2401.15635.pdf 这篇文章是清华和腾讯合作的,前三作都是学校。估计是实验室的老师是专门做对比学习的,然后把对比学习的前沿应用到业务中。引用的对比学习论文有点多,怎么做的说的很明白,就是缝合了两种对比方法,但是不太清楚哪些是真正原创的。
Contrastive learningSelf-supervised learningDual contrastiveVisual representationExisting contrastive methods usually learn visual representations either by maximizing instance contrast or by minimizing dimension redundancy separately, and fail to make full use of data information. In this paper, we propose an ...
In this paper, we propose a novel method based on contrastive learning and a dual learning setting (exploiting two encoders) to infer an efficient mapping between unpaired data. Additionally, while CUT suffers from mode collapse, a variant of our method efficiently addresses this issue. We ...
Dual Contrastive Learning for Unsupervised Image-to-Image Translation Junlin Han, Mehrdad Shoeiby, Lars Petersson, Mohammad Ali Armin DATA61-CSIRO and Australian National University In NTIRE, CVPRW 2021. Our pipeline is quite straightforward. The main idea is a dual setting with two encoders to ca...
PCDC: prototype-assisted dual-contrastive learning with depthwise separable convolutional neural network for few-shot fault diagnosis of permanent magnet s... PCDC: prototype-assisted dual-contrastive learning with depthwise separable convolutional neural network for few-shot fault diagnosis of permanent ...
Dual-stream Multiple Instance Learning Network for Whole Slide Image Classification with Self-supervised Contrastive Learning Bin Li1,2, Yin Li3,4*, Kevin W. Eliceiri1,2,5* 1Department of Biomedical Engineering, University of Wisconsin-Madison 2Morgridge Institu...
Secondly, the Feature Space Global Relationship Invariance (FSGRI) training method is introduced based on supervised contrastive learning. This method maintains the consistency of relationships between sample features with their degradation process during model training, simplifying the subsequently regression ...
Contrastive Trajectory Similarity Learning with Dual-Feature Attention (TrajCL) - ICDE 2023 - changyanchuan/TrajCL
Unpaired Deep Image Deraining Using Dual Contrastive Learning 基于双对比度学习的非配对深度图像脱噪 Abstract 在本文中,建立了一个有效的非配对SID对抗框架,该框架在深度特征空间中,通过双对比学习方式探索非配对样本的相互性质,将其称为DCDGAN。 该方法主要由双向翻译分支(BTB)和对比指导分支(CGB)两个合作分支组成...