UbiEnlight: User-Perception-Aware Real-Time Low-Light Video Enhancement on Mobile Devices and Smartglasses

Low-light video capture is now common on smartphones and wearables, yet dynamic illumination coupled with mobile/werable user motion causes noise, blur, and flicker that make videos hard to perceive and use , especially for users with night blindness and near-eye displays. Prior work enhances frames with post-hoc temporal constraints or optimizes videos directly; however, low-light and motion degradations are spatiotemporally coupled , so post-hoc consistency after per-frame restoration often leaves flicker and motion artifacts. We present UbiEnlight, the first diffusion-transformer-based on-device system for real-time, temporally stable low-light video enhancement. UbiEnlight builds on two insights: (1) illumination and structure separate more robustly in the frequency domain, enabling a spectrum-guided diffusion transformer that injects Fourier amplitude/phase priors to correct illumination while anchoring structure without optical flow; and (2) user perceptual tolerance varies by context, motivating a perception-aware controller that adapts sampling depth, attention reuse, and frame caching at runtime. We implement UbiEnlight on smartphones and smartglasses, and evaluate it against state-of-the-art baselines. UbiEnlight improves temporal stability by up to 54.76% under dynamic/extreme conditions while sustaining real-time on-device performance.

Authors

Institutions

Publication Details

Journal
Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies
Published
2026-09-30
DOI
https://doi.org/10.1145/3832024
Primary Topic
Image and Video Quality Assessment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

UbiEnlight: User-Perception-Aware Real-Time Low-Light Video Enhancement on Mobile Devices and Smartglasses

Minfan Wang, Zimu Zhou, Bin Guo, Sicong Liu et al.
Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies
Image and Video Quality Assessment
article

UbiEnlight: User-Perception-Aware Real-Time Low-Light Video Enhancement on Mobile Devices and Smartglasses

Minfan Wang, Zimu Zhou, Bin Guo, Sicong Liu, Zhiwen Yu, Junzhao Du, Teng Li, Sixun He
article en

Abstract

Low-light video capture is now common on smartphones and wearables, yet dynamic illumination coupled with mobile/werable user motion causes noise, blur, and flicker that make videos hard to perceive and use , especially for users with night blindness and near-eye displays. Prior work enhances frames with post-hoc temporal constraints or optimizes videos directly; however, low-light and motion degradations are spatiotemporally coupled , so post-hoc consistency after per-frame restoration often leaves flicker and motion artifacts. We present UbiEnlight, the first diffusion-transformer-based on-device system for real-time, temporally stable low-light video enhancement. UbiEnlight builds on two insights: (1) illumination and structure separate more robustly in the frequency domain, enabling a spectrum-guided diffusion transformer that injects Fourier amplitude/phase priors to correct illumination while anchoring structure without optical flow; and (2) user perceptual tolerance varies by context, motivating a perception-aware controller that adapts sampling depth, attention reuse, and frame caching at runtime. We implement UbiEnlight on smartphones and smartglasses, and evaluate it against state-of-the-art baselines. UbiEnlight improves temporal stability by up to 54.76% under dynamic/extreme conditions while sustaining real-time on-device performance.

Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous TechnologiesVol. 10(3)
Xidian University (CN), City University of Hong Kong (HK), Northwestern Polytechnical University (CN)
Sustainable cities and communities
Openalex Percentile: Top 14%
Image and Video Quality Assessment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

UbiEnlight: User-Perception-Aware Real-Time Low-Light Video Enhancement on Mobile Devices and Smartglasses — Minfan Wang, Zimu Zhou, et al. · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies (2026) | TGRS Research Map | TGRS