• Corpus ID: 237091273

SOTR: Segmenting Objects with Transformers

@article{Guo2021SOTRSO,
  title={SOTR: Segmenting Objects with Transformers},
  author={Ruohao Guo and Dantong Niu and Liao Qu and Zhenbo Li},
  journal={ArXiv},
  year={2021},
  volume={abs/2108.06747}
}
Most recent transformer-based models show impressive performance on vision tasks, even better than Convolution Neural Networks (CNN). In this work, we present a novel, flexible, and effective transformer-based model for high-quality instance segmentation. The proposed method, Segmenting Objects with TRansformers (SOTR), simplifies the segmentation pipeline, building on an alternative CNN backbone appended with two parallel subtasks: (1) predicting per-instance category via transformer and (2… 

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