Graphonomy: Universal Image Parsing via Graph Reasoning and Transfer

@article{Lin2022GraphonomyUI,
  title={Graphonomy: Universal Image Parsing via Graph Reasoning and Transfer},
  author={Liang Lin and Yiming Gao and Ke Gong and Meng Wang and Xiaodan Liang},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2022},
  volume={44},
  pages={2504-2518}
}
Prior highly-tuned image parsing models are usually studied in a certain domain with a specific set of semantic labels and can hardly be adapted into other scenarios (e.g.sharing discrepant label granularity) without extensive re-training. Learning a single universal parsing model by unifying label annotations from different domains or at various levels of granularity is a crucial but rarely addressed topic. This poses many fundamental learning challenges, e.g.discovering underlying semantic… 
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