什么是“语义分割”与“分割”相比。和“场景标记”？ [英] What is "semantic segmentation" compared to "segmentation" and "scene labeling"?

问题描述

语义分割只是Pleonasm还是语义分割和分割之间有区别吗？ 场景标记或场景解析有什么区别？

像素级和像素级分割之间有什么区别？

（侧面问题：当你有这种像素级的注释，你可以免费获取对象检测，还是还有事情要做？）

请为您的定义指定来源。

使用语义分段的来源

• Jonathan Long，Evan Shelhamer，Trevor Darrell：

  解决方案

  / strong>是将图片分割成多个相干部分，但不会尝试理解这些部分代表的内容。最着名的作品之一（但绝对不是第一个）是 Shi and MalikNormalized Cuts and图像分割PAMI 2000 。这些工作试图根据低级提示，如颜色，纹理和边界的平滑度来定义一致性。您可以将这些作品追溯到格式塔理论。

  
  
  

  另一方面，语义分割试图将图像分割成语义上有意义的部分和以将每个部分分类成预定类之一。您也可以通过分类每个像素（而不是整个图像/段）实现相同的目标。在这种情况下，你正在进行逐像素分类，这导致相同的最终结果，但在一个稍微不同的路径...

  
  
  

  所以，我想你可以说语义分割，场景标记和像素分类基本上试图实现相同的目标：语义地理解每个像素在图像中的作用。你可以采取许多路径达到这个目标，这些路径导致术语中的细微差别。

  
  

  Is semantic segmentation just a Pleonasm or is there a difference between "semantic segmentation" and "segmentation"? Is there a difference to "scene labeling" or "scene parsing"?

  What is the difference between pixel-level and pixelwise segmentation?

  (Side-question: When you have this kind of pixel-wise annotation, do you get object detection for free or is there still something to do?)

  Please give a source for your definitions.

  Sources which use "semantic segmentation"

  • Jonathan Long, Evan Shelhamer, Trevor Darrell: Learning Deconvolution Network for Semantic Segmentation. CVPR, 2015.
  • Hong, Seunghoon, Hyeonwoo Noh, and Bohyung Han: "Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation." arXiv preprint arXiv:1506.04924, 2015.
  • V. Lempitsky, A. Vedaldi, and A. Zisserman: A pylon model for semantic segmentation. In Advances in Neural Information Processing Systems, 2011.

  Sources which use "scene labeling"

  • Clement Farabet, Camille Couprie, Laurent Najman, Yann LeCun: Learning Hierarchical Features for Scene Labeling. In Pattern Analysis and Machine Intelligence, 2013.

  Source which use "pixel-level"

  • Pinheiro, Pedro O., and Ronan Collobert: "From Image-level to Pixel-level Labeling with Convolutional Networks." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015. (see http://arxiv.org/abs/1411.6228)

  Source which use "pixelwise"

  • Li, Hongsheng, Rui Zhao, and Xiaogang Wang: "Highly efficient forward and backward propagation of convolutional neural networks for pixelwise classification." arXiv preprint arXiv:1412.4526, 2014.

  Google Ngrams

  "Semantic segmentation" seems to be more used recently than "scene labeling"

  解决方案

  "segmentation" is a partition of an image into several "coherent" parts, but without any attempt at understanding what these parts represent. One of the most famous works (but definitely not the first) is Shi and Malik "Normalized Cuts and Image Segmentation" PAMI 2000. These works attempt to define "coherence" in terms of low-level cues such as color, texture and smoothness of boundary. You can trace back these works to the Gestalt theory.

  On the other hand "semantic segmentation" attempts to partition the image into semantically meaningful parts, and to classify each part into one of the pre-determined classes. You can also achieve the same goal by classifying each pixel (rather than the entire image/segment). In that case you are doing pixel-wise classification, which leads to the same end result but in a slightly different path...

  So, I suppose you can say that "semantic segmentation", "scene labeling" and "pixelwise classification" are basically trying to achieve the same goal: semantically understanding the role of each pixel in the image. You can take many paths to reach that goal, and these paths lead to slight nuances in the terminology.

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