TRACE achieves 0.998 mIoU for CO2 plume segmentation and best-in-class flux classification from MWIR thermal videos via a gas-aware attention encoder and temporal fusion module.
Exploiting temporal state space sharing for video se- mantic segmentation
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DiTTA distills SAM2 temporal segmentation knowledge into image models via efficient test-time adaptation and a lightweight fusion module to produce annotation-free video semantic segmentation that matches or exceeds fully supervised performance.
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TRACE: Thermal Recognition Attentive-Framework for CO2 Emissions from Livestock
TRACE achieves 0.998 mIoU for CO2 plume segmentation and best-in-class flux classification from MWIR thermal videos via a gas-aware attention encoder and temporal fusion module.
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Bootstrapping Video Semantic Segmentation Model via Distillation-assisted Test-Time Adaptation
DiTTA distills SAM2 temporal segmentation knowledge into image models via efficient test-time adaptation and a lightweight fusion module to produce annotation-free video semantic segmentation that matches or exceeds fully supervised performance.