SAM-MT: Real-Time Interactive Multi-Target Video Segmentation
Modern Video Object Segmentation (VOS) involves tracking and segmenting user-specified targets. While recent approaches have achieved remarkable performance in single-target scenarios, extending them to multi-target settings typically involves replicating the single-target processing for each individual object, resulting in reduced frame rates (FPS) with unbounded latency as target count increases. Built upon Segment Anything 2 (SAM2), we propose SAM-MT, which addresses this by transforming the model into an interactive framework for real-time Multi-Target video segmentation. SAM-MT uses expli
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- PossiblePossibly related (embedding) · 50%Somnusochi/VLM-AutoYOLO →
- LinkedLinked via arxiv author · 85%Ruiqi Shen →
“SAM-MT: Real-Time Interactive Multi-Target Video Segmentation”
- LinkedLinked via arxiv author · 85%Chang Liu →
“SAM-MT: Real-Time Interactive Multi-Target Video Segmentation”
- LinkedLinked via arxiv author · 85%Henghui Ding →
“SAM-MT: Real-Time Interactive Multi-Target Video Segmentation”