StableFlow: Real-Time 4K Video Super-Resolution with Robust Feature Propagation.

Authors

Kemi Chen, Xianbin Zhang, Aiping Huang, Wei Gao, Tiesong Zhao

Published in

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. Volume PP. Sep 04, 2026. Epub Sep 04, 2026.

Abstract

Real-time 4K video super-resolution (VSR) requires the effective reuse of temporal information under strict latency constraints, typically relying on temporal alignment and real-time reconstruction. However, imperfect alignment introduces perturbations into the temporal recursion, which can accumulate over time and degrade reconstruction quality-an effect widely observed in recurrent VSR pipelines but rarely analyzed explicitly from a dynamical perspective under real-time constraints. In this work, we formulate real-time VSR inference as a recurrent dynamical process, embedding alignment within the state update. This formulation enables explicit analysis of how alignment-induced perturbations are introduced and propagated during inference. Motivated by this analysis, we propose StableFlow, a stability-guided real-time VSR framework. Specifically, StableFlow introduces an Alignment Gain-aware Alignment Module (AGAM) to enhance the utility of temporally aligned features, a State-aware Perturbation Control Filter (SPCF) to suppress unreliable propagated information, and a Temporal Propagation Control (TPC) loss to regulate long-term recurrent state evolution. Our method combines efficient temporal alignment with state-aware perturbation control and a temporal propagation control loss to stabilize long-term recurrent behavior. Experiments demonstrate that StableFlow achieves real-time 4K performance (over 40 FPS on an NVIDIA RTX 3090) for 4×upscaling from 960×540 inputs to 3840×2160 outputs, with only 321K parameters and 77.45G FLOPs, while maintaining competitive reconstruction quality. The source code will be made public after the peer review process.

PMID:
42696631
Bibliographic data and abstract were imported from PubMed on 05 Sep 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.