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Segment objects at many granularities by generating masks at multiple levels with Semantic-SAM

Segment objects at many granularities by generating masks at multiple levels with Semantic-SAM


Semantic-SAM: Segment and Recognize Anything at Any Granularity

arXiv paper abstract https://arxiv.org/abs/2307.04767



... introduce Semantic-SAM, a universal image segmentation model to enable segment and recognize anything at any desired granularity.


... model offers two key advantages: semantic-awareness and granularity-abundance.


To achieve semantic-awareness ... consolidate multiple datasets across three granularities and introduce decoupled classification for objects and parts.


This allows ... model to capture rich semantic information.


For the multi-granularity capability ... propose a multi-choice learning scheme during training, enabling each click to generate masks at multiple levels that correspond to multiple ground-truth masks.


... demonstrate that ... model successfully achieves semantic-awareness and granularity-abundance ...



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