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Found 6 papers, 4 papers with code
Diffusion-based Iterative Counterfactual Explanations for Fetal Ultrasound Image Quality Assessment
Obstetric ultrasound image quality is crucial for accurate diagnosis and monitoring of fetal health.
Fast Diffusion-Based Counterfactuals for Shortcut Removal and Generation
Via a novel inpainting-based modification we spatially limit the changes made with no extra inference step, encouraging the removal of spatially constrained shortcut features while ensuring that the shortcut-free counterfactuals preserve their remaining image features to a high degree.
Are Sex-based Physiological Differences the Cause of Gender Bias for Chest X-ray Diagnosis?
In this work, we investigate the causes of gender bias in machine learning-based chest X-ray diagnosis.
AIM 2020 Challenge on Image Extreme Inpainting
This report focuses on proposed solutions and results for two different tracks on extreme image inpainting: classical image inpainting and semantically guided image inpainting.
GramGAN: Deep 3D Texture Synthesis From 2D Exemplars
Inspired by recent advances in natural texture synthesis, we train deep neural models to generate textures by non-linearly combining learned noise frequencies.
Image Restoration using Plug-and-Play CNN MAP Denoisers
Plug-and-play denoisers can be used to perform generic image restoration tasks independent of the degradation type.
