The first paired POCUS-to-high-end ultrasound dataset is released and a cGAN baseline raises SSIM from 0.29 to 0.54 and PSNR from 19.16 dB to 22.41 dB on 1064 test pairs.
Image-to-Image Translation with Conditional Adversarial Networks
8 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 8representative citing papers
VitaminP uses paired H&E-mIF data to train a model that transfers molecular boundary information, enabling accurate whole-cell segmentation directly from routine H&E histology across 34 cancer types.
A new large-scale synthetic multi-task benchmark dataset supplying pixel-perfect depth, domain-shifted night imagery, and multi-scale low-resolution pairs for aerial remote sensing.
Three style-based neural architectures are proposed for real-time weather classification from images, with two truncated ResNet variants claimed to outperform prior methods and generalize across public datasets.
ST-STORM introduces a dual-branch SSL framework that disentangles semantic content from stylistic appearance using gated latent streams, JEPA for content invariance, and adversarial constraints for style capture.
Lightweight multi-task models using Gram matrices and PatchGAN-style architectures detect 53 weather classes from RGB images with F1 scores above 96% internally and 78% zero-shot externally, supported by a new 503k-image dataset.
VCC-DSA uses a vascular consistency constraint and self-evolving training data to suppress motion artifacts in DSA, reporting 73.4% PSNR and 8.56% SSIM gains over other methods.
A conditional Wasserstein GAN generates plausible future SWI drought trajectories for French insurance risk management under climate change.
citing papers explorer
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A Paired Point-of-Care Ultrasound Dataset for Image Quality Enhancement and Benchmarking via a cGAN Baseline
The first paired POCUS-to-high-end ultrasound dataset is released and a cGAN baseline raises SSIM from 0.29 to 0.54 and PSNR from 19.16 dB to 22.41 dB on 1064 test pairs.
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VitaminP: cross-modal learning enables whole-cell segmentation from routine histology
VitaminP uses paired H&E-mIF data to train a model that transfers molecular boundary information, enabling accurate whole-cell segmentation directly from routine H&E histology across 34 cancer types.
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SyMTRS: Benchmark Multi-Task Synthetic Dataset for Depth, Domain Adaptation and Super-Resolution in Aerial Imagery
A new large-scale synthetic multi-task benchmark dataset supplying pixel-perfect depth, domain-shifted night imagery, and multi-scale low-resolution pairs for aerial remote sensing.
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Style-Based Neural Architectures for Real-Time Weather Classification
Three style-based neural architectures are proposed for real-time weather classification from images, with two truncated ResNet variants claimed to outperform prior methods and generalize across public datasets.
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Stylistic-STORM (ST-STORM) : Perceiving the Semantic Nature of Appearance
ST-STORM introduces a dual-branch SSL framework that disentangles semantic content from stylistic appearance using gated latent streams, JEPA for content invariance, and adversarial constraints for style capture.
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Heuristic Style Transfer for Real-Time, Efficient Weather Attribute Detection
Lightweight multi-task models using Gram matrices and PatchGAN-style architectures detect 53 weather classes from RGB images with F1 scores above 96% internally and 78% zero-shot externally, supported by a new 503k-image dataset.
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VCC-DSA: A Novel Vascular Consistency Constrained DSA Imaging Model for Motion Artifact Suppression
VCC-DSA uses a vascular consistency constraint and self-evolving training data to suppress motion artifacts in DSA, reporting 73.4% PSNR and 8.56% SSIM gains over other methods.
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A Wasserstein GAN-based climate scenario generator for risk management and insurance: the case of soil subsidence
A conditional Wasserstein GAN generates plausible future SWI drought trajectories for French insurance risk management under climate change.