We address this problem with heuristic attention pixel-level contrastive loss for representation learning (HAPiCLR), a self-supervised joint embedding contrastive framework that operates at the pixel level and makes use of heuristic mask information. HAPiCLR leverages pixel-level information from the ...
Pixel-level vs. image-level 在这一实验中,文章将PCD的最后输出又做了一次全局平均池化,得到了image-level的PCD变体(保持了其他所有设置一致)。目的是为了更公平地对比pixel-level和image-level的蒸馏信号的效果。实验结果表明,pixel-level的蒸馏信号确实是PCD有效的关键。 SpatialAdaptor 文章针对SA做了4种变体:(a)...
Furthermore, HAPiCLR loss combined with other contrastive objectives such as SimCLR or MoCo loss produces considerable performance boosts on all downstream tasks, including image classification, object detection, and instance segmentation. 展开 关键词: Pixel-level contrastive learning Pixel-level attention ...
这篇文章主要是通过大量的实验研究,针对目前关于pixel-level输入的状态表征提取方法进行了对比分析,指出其中关于表征提取最重要的是预测reward和transition的能力,并提出了一种简单有效的表征提取方法。该论文最大的优势在于其通过大量的实验验证对状态表征提取方法进行了较为全面的梳理总结,但由于所提方法创新性不足,其在...
we compute the language-image contrastive loss as [64]. We take the last valid token feature of Qt from the text encoder to represent a text as qˆ t and take the last entry in Os derived from X-Decoder as oˆ s . As a result, we obtain B pairs of features hqˆ t i , ...
To solve this problem, we propose a new self-supervised learning method, called multi-scale fusion pixel and instance contrastive learning network (MPINet). This method first uses focal frequency loss to optimize the learning of high-level semantic information, and then strengthens the spatial ...
contrastive cycle-consistency loss on the level of pixels. Fi- nally, [56] performs image-to-image translation for UDA in frequency space rather than pixel space using a Fourier transform. Beyond cycle-consistency, [12] enforces cross-domain consistent predic...
Some latest studies [41, 33, 71] also confirm label information can assist con- trastive learning based image-level pattern pre-training. We raise a pixel-to-pixel contrastive learning method for semantic segmentation in the fully supervised setting. It yields a new t...
2009, which presents training examples progressively for a specific task, our strategy applies curriculum learning at a task level. Such a design is based on the observation that grid classification on heatmaps becomes easier when the stride of the network becomes larger. This is easy to ...
4.1). The gray level that maps into the output pixel at (x, y) is uniquely determined by interpolation among these four input pixels. Some output pixels may map to locations that fall outside the borders of the input image. In this case an arbitrary constant gray level (e.g., zero) ...