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Fast and Faithful: Principled Conditional Flow Matching for Inverse Problems

Paper recorded by Signals 4 on 2026-09-11 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-11 on arXiv · recorded by Signals 4 on 2026-09-14

Category: cs.CV · 计算机视觉 · first seen 2026-09-14

Abstract

Flow matching approaches to imaging inverse problems commonly incorporate measurements in two ways. Conditioning-based approaches supply measurement-derived information as a network input, often through concatenation, while inference-guided approaches combine an unconditional velocity field with a separate data-consistency update. In these common formulations, the forward model is not explicitly e

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#67 most recent of 237 cs.CV papers we have recorded · ↑ newer: Generative Retrieval for Unsupervised Text-Based Person Search · ↓ older: DementiaCare-Bench: A Modality-Validated Video Benchmark
Cite this page: Fast and Faithful: Principled Conditional Flow Matching for Inverse Problems: the #67 most recent of 237 cs.CV papers we have recorded (as of 2026-09-11). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/fast-and-faithful-principled-conditional-flow-matching-for-inverse-problems.html
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