3 papers
cs.CV2026
RS-Prune: Read-Sparse, Store-Sparse Token Pruning for Video Object Segmentation
Avilasha Mandal, Sarvesh Shashikumar
We introduce RS-Prune, a training-free token-pruning recipe that instantiates as a small set of inference time hooks atop existing video object segmentation (VOS) networks. Mod…
cs.CV2026
VGGT-SLAM++
Avilasha Mandal, Rajesh Kumar, Sudarshan Sunil Harithas +1
We introduce VGGT-SLAM++, a complete visual SLAM system that leverages the geometry-rich outputs of the Visual Geometry Grounded Transformer (VGGT). The system comprises a visual o…
cs.CV2025
Fast SAM2 with Text-Driven Token Pruning
Avilasha Mandal, Chaoning Zhang, Fachrina Dewi Puspitasari +6
Segment Anything Model 2 (SAM2), a vision foundation model has significantly advanced in prompt-driven video object segmentation, yet their practical deployment remains limited by…