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Generating Chest X-Ray Counterfactuals by Specialising Foundation Image Models

Paper recorded by Signals 4 on 2026-09-21 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-21 on arXiv · recorded by Signals 4 on 2026-09-22

Category: cs.CV · 计算机视觉 · first seen 2026-09-22

Abstract

Counterfactual image generation answers questions about how a subject would have looked under retrospective, hypothetical scenarios. Recent methods have improved perceptual quality, identity preservation and faithfulness to an underlying causal model, but their adoption in healthcare is limited by scarce annotated data, distribution shift between datasets, and mismatches between pretrained generat

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#5 most recent of 270 cs.CV papers we have recorded · ↑ newer: PixelDiT2: Representation-Grounded Pixel Diffusion Transformers · ↓ older: SPHQuant: Efficient extreme low bit weight quantization for Vision-Lan
Cite this page: Generating Chest X-Ray Counterfactuals by Specialising Foundation Image Models: the #5 most recent of 270 cs.CV papers we have recorded (as of 2026-09-21). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/generating-chest-x-ray-counterfactuals-by-specialising-foundation-image-models.html
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