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Isomer: Isomerous Transformer for Zero-shot Video Object Segmentation vs SegPrompt: Boosting Open-world Segmentation via Category-level Prompt Learning
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Isomer: Isomerous Transformer for Zero-shot Video Object Segmentation
Recent leading zero-shot video object segmentation (ZVOS) works devote to integrating appearance and motion information by elaborately designing feature fusion modules and identically applying them in multiple feature stages.
SegPrompt: Boosting Open-world Segmentation via Category-level Prompt Learning
In this work, we propose a novel training mechanism termed SegPrompt that uses category information to improve the model's class-agnostic segmentation ability for both known and unknown categories.
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Isomer: Isomerous Transformer for Zero-shot Video Object Segmentation vs Zugrow
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