Signals 4 · free daily AI digest

Diffusion Plug-in Priors for Self-Supervised Ultrasound Video Restoration

Paper recorded by Signals 4 on 2026-11-03 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-11-03 on arXiv · recorded by Signals 4 on 2026-11-04

Category: cs.CV · 计算机视觉 · first seen 2026-11-04

Abstract

\textit{Objective:} Ultrasound videos are limited by hardware-constrained spatial resolution and signal-dependent speckle, while paired low- and high-resolution acquisitions for supervised restoration are rarely available. We aim to jointly super-resolve and despeckle ultrasound videos without paired training data or network retraining. \textit{Methods:} We propose UltraDiff, which uses a frozen p

Read on arXiv →

#12 most recent of 710 cs.CV papers we have recorded · ↑ newer: PLANTEUR: A Crop-Type Segmentation Benchmark for Tropical Regions · ↓ older: TAQ-MOTR: Tracking-Aware Detection Query Formation for End-to-End Mult
Cite this page: Diffusion Plug-in Priors for Self-Supervised Ultrasound Video Restoration: the #12 most recent of 710 cs.CV papers we have recorded (as of 2026-11-03). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/diffusion-plug-in-priors-for-self-supervised-ultrasound-video-restoration.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
Related: More cs.CV papers · arXiv signals · All papers · Today in AI
Get 4 AI signals a day by email — free.
Subscribe free → See all plans →
Get 4 AI signals a day by email — free
All models · All repos · By company · Daily editions