SLAMs: Semantic Learning based Activation Map for Weakly Supervised Semantic Segmentation
Shenzhen University（深圳大学）
英文摘要：
Recent mainstream weakly-supervised semantic segmentation (WSSS) approaches mainly relies on image-level classification learning, which has limited representation capacity. In this paper, we propose a novel semantic learning based framework, named SLAMs (Semantic Learning based Activation Map), for WSSS.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
