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Blind Video Denoising for Vocal Tract rtMRI using a Self-Supervised Ensemble

Paper recorded by Signals 4 on 2026-10-29 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-29 on arXiv · recorded by Signals 4 on 2026-10-30

Category: cs.CV · 计算机视觉 · first seen 2026-10-30

Abstract

Real-time magnetic resonance imaging of the vocal tract makes speech articulation directly observable, but the trade-off between temporal resolution and signal quality introduces substantial noise and obscures fine articulatory detail. Since clean references cannot be acquired for a moving vocal tract, supervised denoising approaches are not applicable in this setting. We propose a self-supervised

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#67 most recent of 710 cs.CV papers we have recorded · ↑ newer: Greenscapes: Optimized Vegetation Configurations in Cities · ↓ older: Mind The Gap (MTG-AD): Dataset and Fine-grained Evaluation for End-to-
Cite this page: Blind Video Denoising for Vocal Tract rtMRI using a Self-Supervised Ensemble: the #67 most recent of 710 cs.CV papers we have recorded (as of 2026-10-29). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/blind-video-denoising-for-vocal-tract-rtmri-using-a-self-supervised-ensemble.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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