OT-Bridge Editor uses geometrically constrained entropic optimal transport to synthesize CAG images with precise stenosis, improving downstream detection by 27.8% on ARCADE and 23.0% on a multi-center dataset.
Semantic image synthesis via diffusion models
7 Pith papers cite this work. Polarity classification is still indexing.
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A generative semantic communication system that sends compressed semantic information and uses diffusion models with spatially-adaptive normalizations to reconstruct high-quality, semantically consistent images even under severe channel noise.
CHIS lets pretrained diffusion models generate structurally controlled histopathology images without any training by frequency-domain initialization and wavelet-based textural modulation.
T-CLIP introduces a physics-aware thermal captioning dataset (IR-Cap) and a decoupled dual-LoRA adaptation of CLIP that improves cross-modal retrieval on thermal benchmarks by separating scene-level and object-level thermal understanding.
A privacy-preserving thermal-only crowd counting framework extracts enhanced features from thermal images via single-step LCM denoising in a depth-to-RGB diffusion model and matches RGB-T fusion performance without RGB input at inference.
SPADE-LDM conditional synthesis from composite semantic masks produces realistic 3D LGE MRI that raises LA cavity Dice from 0.908 to 0.936.
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Generative Semantic Communication: Diffusion Models Beyond Bit Recovery
A generative semantic communication system that sends compressed semantic information and uses diffusion models with spatially-adaptive normalizations to reconstruct high-quality, semantically consistent images even under severe channel noise.