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Achieving a new state-of-the-art mIoU of 38.8% in semantic scene completion with a single-sweep, single-sample approach reveals the power of generative diffusion methods in handling extreme class imbalance.
By leveraging unmixing-informed spectral prompts, USP-Mamba achieves superior hyperspectral image reconstruction while maintaining spatial continuity and contextual integrity.
