自监督视觉表示学习方法依赖于实例识别(instance discrimination,ID)的代理任务(pretext task)。ID任务具有隐式语义一致性(semantic consistency,SC)假设,这在不受约束的数据集中可能是不成立的。 在本文中,作者提出了一种对比掩模预测(contrastive mask prediction,CMP)任务,并设计了一个MaskCo框架来实现该任务。MaskCo...
We point out that the ID task has an implicit semantic consistency (SC) assumption, which may not hold in unconstrained datasets. In this paper, we propose a novel contrastive mask prediction (CMP) task for visual representation learning and design a mask contrast (MaskCo) framework to ...
3.1. The Contrastive Mask Prediction Task 给定一张图片,一个小区域首先被mask掉,然后输入到神经网络中进行处理。训练目标是获得输入图片的特征表示,由此来预测mask的区域。掩模预测任务涉及一个基本假设,即内容与其上下文之间存在相关性 ,作者认为这通常对自然信号都是有效的,包括语言和图像。然而,预测过程对于文本的...
To address the above problem, we propose mask prediction (MaskPre) as a pretext task for unsupervised re-ID, such that the clustering network can capture more semantic information and separate the images into semantic clusters automatically. Specifically, MaskPre masks region-level features with ...
2.1. The Contrastive Mask Prediction Task 给定一张图片,一个小区域首先被mask掉,然后输入到神经网络中进行处理。训练目标是获得输入图片的特征表示,由此来预测mask的区域。掩模预测任务涉及一个基本假设,即内容与其上下文之间存在相关性,作者认为这通常对自然信号都是有效的,包括语言和图像。
Please bear in mind that you should take this and any other prediction with a grain of salt since predicting anything is a thankless task, let alone predicting the future of a novel, highly volatile financial asset like Mask Network.Now, let’s head into it. Before we delve deep into the...
提出了 contrastive mask prediction(CMP)for visual representation learning and design a mask contrast(MaskCo) framework to address. Idea:We make the task contrastive so that the extracted features can focus on high-level semantic meanings instead of pixellevel details. ...
对于head部分也和之前的工作大致一致,只是额外加了一个mask prediction分支。如下图所示是两种不同的head结构,其中RoI是从ResNet的conv4输出的feature上计算的,左图是在Faster R-CNN的基础上增加mask分支,其中RoI先经过res 5之后才分为三个分支,而右边的图是Faster R-CNN + RPN,因为RPN中已经包含了res 5,所以...
mask prediction, or restore the occluded facial part by generative models. However, the former lacks visual results for model interpretation, while the latter suffers from artifacts which may affect downstream recognition. Therefore, this paper proposes a Multi-task gEnerative mask dEcoupling face ...
we expect that emotions for faces in masks with black colors and angular patterns are more likely to be misattributed as negative, whereas emotions for faces in masks with white colors and curved patterns are more likely to be misattributed as positive. This prediction is based on the above-...