A weakly-supervised image quality transfer method generates synthetic distorted DWI images from quality labels to train improved distortion correction models for prostate MRI.
Willcocks, and Toby P
12 Pith papers cite this work. Polarity classification is still indexing.
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ChangeBridge introduces a drift-asynchronous diffusion bridge with composed initialization, pixel-wise drift maps, and drift-aware denoising to produce spatially and temporally coherent post-event remote sensing images.
UniSim learns a universal real-world simulator from orchestrated diverse datasets, enabling zero-shot deployment of policies trained purely in simulation.
A saliency-guided warp-unwarp method reallocates spatial representation to preserve fine structures in latent diffusion models for image-to-image translation.
Adversarial fine-tuning lets single-cell foundation models translate between unpaired ST and scRNA-seq, outperforming existing multi-omics translation methods.
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.
InkDiffuser generates high-fidelity one-shot Chinese calligraphy using high-frequency enhancement and a differentiable ink structure loss for realistic stroke and ink rendering.
GenFocal uses probabilistic ML to downscale coarse climate projections to fine-scale weather events without paired training data and samples rare high-impact events more accurately than prior methods.
ByG enables unpaired training of flow matching editing models by pairing self-extracted instruction-following cues with cycle-consistency and routing gradients from clean predictions to noisy states.
A conditional U-Net with weather conditioning at the bottleneck plus pre- and post-processing translates aerial RGB to thermal images, reaching PSNR 14.55, SSIM 0.81, LPIPS 0.17 and outperforming the ThermalGen baseline on a held-out test set.
MedShift applies flow matching and Schrödinger bridges for class-conditional unpaired translation between synthetic and real skull X-rays, benchmarked on the new X-DigiSkull dataset.
citing papers explorer
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Learning to Distort: Weakly-Supervised Image Quality Transfer for Prostate DWI Correction
A weakly-supervised image quality transfer method generates synthetic distorted DWI images from quality labels to train improved distortion correction models for prostate MRI.
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ChangeBridge: Spatiotemporal Image Generation with Multimodal Controls for Remote Sensing
ChangeBridge introduces a drift-asynchronous diffusion bridge with composed initialization, pixel-wise drift maps, and drift-aware denoising to produce spatially and temporally coherent post-event remote sensing images.
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Learning Interactive Real-World Simulators
UniSim learns a universal real-world simulator from orchestrated diverse datasets, enabling zero-shot deployment of policies trained purely in simulation.
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WarpI2I: Image Warping for Image-to-Image Translation
A saliency-guided warp-unwarp method reallocates spatial representation to preserve fine structures in latent diffusion models for image-to-image translation.
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Single-Cell Cross-Modal Transfer by Adversarial Fine-Tuning of Foundation Models
Adversarial fine-tuning lets single-cell foundation models translate between unpaired ST and scRNA-seq, outperforming existing multi-omics translation methods.
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T-CLIP: Enabling Thermal Perception for Contrastive Language-Image Pretraining
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.
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Thermal-Only Crowd Counting with Deployment-Time Privacy Protection
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.
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InkDiffuser: High-Fidelity One-shot Chinese Calligraphy via Differentiable Morphological Optimization
InkDiffuser generates high-fidelity one-shot Chinese calligraphy using high-frequency enhancement and a differentiable ink structure loss for realistic stroke and ink rendering.
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Regional climate risk assessment from climate models using probabilistic machine learning
GenFocal uses probabilistic ML to downscale coarse climate projections to fine-scale weather events without paired training data and samples rare high-impact events more accurately than prior methods.
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Bootstrap Your Generator: Unpaired Visual Editing with Flow Matching
ByG enables unpaired training of flow matching editing models by pairing self-extracted instruction-following cues with cycle-consistency and routing gradients from clean predictions to noisy states.
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A Conditional U-Net Pipeline with Pre- and Post-Processing for Aerial RGB-to-Thermal Image Translation
A conditional U-Net with weather conditioning at the bottleneck plus pre- and post-processing translates aerial RGB to thermal images, reaching PSNR 14.55, SSIM 0.81, LPIPS 0.17 and outperforming the ThermalGen baseline on a held-out test set.
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MedShift: Implicit Conditional Transport for X-Ray Domain Adaptation
MedShift applies flow matching and Schrödinger bridges for class-conditional unpaired translation between synthetic and real skull X-rays, benchmarked on the new X-DigiSkull dataset.