Abstract
This paper presents a fresh perspective on the role of saliency maps in weakly-supervised semantic segmentation (WSSS) and offers new insights and research directions based on our empirical findings. We conduct comprehensive experiments and observe that the quality of the saliency map is a critical factor in saliency-guided WSSS approaches. Nonetheless, we find that the saliency maps used in previous works are often arbitrarily chosen, despite their significant impact on WSSS. Additionally, we observe that the choice of the threshold, which has received less attention before, is non-trivial in WSSS. To facilitate more meaningful and rigorous research for saliency-guided WSSS, we introduce \texttt{WSSS-BED}, a standardized framework for conducting research under unified conditions. \texttt{WSSS-BED} provides various saliency maps and activation maps for seven WSSS methods, as well as saliency maps from unsupervised salient object detection models.
Abstract (translated)
本文从新的角度探讨了显著图在弱监督语义分割（WSSS）中的作用，并基于我们的实证研究提供了新的见解和研究方向。我们进行了全面的实验，并观察到显著图的质量对显著引导的WSSS方法至关重要。然而，我们发现之前的工作使用的显著图通常是随意选择的，尽管它们对WSSS具有重要影响。此外，我们观察到在WSSS中选择阈值是一个非 trivial的问题。为了促进更有意义和严谨的研究，我们引入了\texttt{WSSS-BED}，一个在统一条件下进行研究的标准框架。\texttt{WSSS-BED}为七个WSSS方法提供了各种显著图和激活图，以及来自无监督显著物体检测模型的显著图。
URL
https://arxiv.org/abs/2404.00918
