A modified video segmentation architecture decouples processing latency from target count, enabling real-time (>36 FPS) tracking of 10+ objects simultaneously while preserving individual identities.
Video object segmentation using space-time memory networks
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.CV 2years
2026 2roles
background 1polarities
background 1representative citing papers
M⁴-SAM equips SAM2 with modality-aware MoE-LoRA, gated multi-level fusion, and pseudo-guided initialization to reach state-of-the-art on RGB-D video salient object detection.
citing papers explorer
-
SAM-MT: Real-Time Interactive Multi-Target Video Segmentation
A modified video segmentation architecture decouples processing latency from target count, enabling real-time (>36 FPS) tracking of 10+ objects simultaneously while preserving individual identities.
-
M$^4$-SAM: Multi-Modal Mixture-of-Experts with Memory-Augmented SAM for RGB-D Video Salient Object Detection
M⁴-SAM equips SAM2 with modality-aware MoE-LoRA, gated multi-level fusion, and pseudo-guided initialization to reach state-of-the-art on RGB-D video salient object detection.