Seamless Scene Segmentation

CVPR 2019 Lorenzo PorziSamuel Rota BulòAleksander ColovicPeter Kontschieder

In this work we introduce a novel, CNN-based architecture that can be trained end-to-end to deliver seamless scene segmentation results. Our goal is to predict consistent semantic segmentation and detection results by means of a panoptic output format, going beyond the simple combination of independently trained segmentation and detection models... (read more)

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