SENSE is the first stereo open-vocabulary semantic segmentation method that uses vision-language models and stereo geometry to achieve better phrase-grounded segmentation and generalization on benchmarks like Cityscapes and KITTI.
Masked-attention mask transformer for universal image segmentation
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SENSE: Stereo OpEN Vocabulary SEmantic Segmentation
SENSE is the first stereo open-vocabulary semantic segmentation method that uses vision-language models and stereo geometry to achieve better phrase-grounded segmentation and generalization on benchmarks like Cityscapes and KITTI.