Segmenting objects in images with transformers
Segmenting objects in images with transformers
SOTR: Segmenting Objects with Transformers
arXiv paper abstract https://arxiv.org/abs/2108.06747
arXiv PDF paper https://arxiv.org/pdf/2108.06747.pdf
Most recent transformer-based models show impressive performance on vision tasks, even better than Convolution Neural Networks (CNN).
... present a novel, flexible, and effective transformer-based model for high-quality instance segmentation.
... SOTR can effectively extract lower-level feature representations and capture long-range context dependencies by Feature Pyramid Network (FPN) and twin transformer, respectively.
... proposed twin transformer is time- and resource-efficient since only a row and a column attention are involved to encode pixels.
... SOTR is easy to be incorporated with various CNN backbones and transformer model variants
... SOTR performs well on the MS COCO dataset and surpasses state-of-the-art instance segmentation approaches. ...
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