DiffVAS combines diffusion-based reconstruction of unobserved geospatial regions with target-conditioned RL planning to enable multi-object visual active search in partially observable environments.
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2026 2verdicts
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MAST is a mask-guided attention allocation method that enables artifact-free multi-style transfer in diffusion models by anchoring layout, distributing attention mass, scaling sharpness, and injecting details.
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DiffVAS: Diffusion-Guided Visual Active Search in Partially Observable Environments
DiffVAS combines diffusion-based reconstruction of unobserved geospatial regions with target-conditioned RL planning to enable multi-object visual active search in partially observable environments.
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MAST: Mask-Guided Attention Mass Allocation for Training-Free Multi-Style Transfer
MAST is a mask-guided attention allocation method that enables artifact-free multi-style transfer in diffusion models by anchoring layout, distributing attention mass, scaling sharpness, and injecting details.