Temporal Consistency in Video Restoration

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12 papers1 paper in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

Taming Noise Initialization for Zero-shot Video Restoration with Image Diffusion Priors
Oct 27, 2026Chong Wang, Zixuan Fu, Hao Cheng +3Temporal Consistency in Video Restoration Video Restoration
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore · School of Artificial Intelligence, Hebei University of Technology, Tianjin, China · Division of Robotics, Perception and Learning, KTH Royal Institute of Technology, Stockholm, Sweden +1
LoCoVSR: Local Context Diffusion Posterior Sampling for Video Super-Resolution
Sep 26, 2026Matan Ben Chorin, Michael EladTemporal Consistency in Video Restoration Video Super-Resolution
Faculty of Electrical and Computer Engineering Technion - Israel Institute of Technology Haifa, Israel · Faculty of Computer Science Department Technion - Israel Institute of Technology Haifa, Israel
Zero-Shot Video Restoration and Enhancement with Text-to-Image Latent Diffusion Models and Multi-Modal References
Aug 27, 2026Cong Cao, Huanjing Yue, Xin Liu +1Temporal Consistency in Video Restoration Video Restoration
School of Electrical and Information Engineering, Tianjin University, Tianjin, China · Computer Vision and Pattern Recognition Laboratory, School of Engineering Science, Lappeenranta-Lahti University of Technology LUT, Lappeenranta, Finland
RealVDeblur: One-Step Diffusion for Generalizable Real-World Video Deblurring
Jul 22, 2026Renbiao Jin, Mingxin Yang, Yutian Chen +8Video Diffusion Models Temporal Consistency in Video Restoration
1Shanghai Jiao Tong University · 2Shanghai AI Laboratory · 3CUHK MMLab +2
LPM: Industrial-Scale Generative Video Restoration
Jul 15, 2026Bichuan Zhu, Fulin Li, Jiachao Gong +14Video Diffusion Models Temporal Consistency in Video Restoration
LPM Team, Kuaishou Technology
FADRA: Frequency-Aware Diffusion with Residual Adaptation for Video Face Restoration
Jul 7, 2026Jin Jiang, Jia Wang, Panwen Hu +2Diffusion Model Adaptation Video Diffusion Models
College of Information Technology (CIT), United Arab Emirates University (UAEU), Al Ain, Abu Dhabi, United Arab Emirates · State Key Laboratory of Physical Oceanography and the Faculty of Information Science and Engineering, Ocean University of China (OUC), Shandong, 266100, China · Computer Vision Department, Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), Abu Dhabi, United Arab Emirates
RGFVR: Reference-Guided Face Video Restoration with Flow Matching
Jun 15, 2026Cem Eteke, Batuhan Tosun, Eckehard SteinbachVideo Diffusion Models Video Restoration
Chair of Media Technology Munich Institute of Robotics and Machine Intelligence School of Computation, Information, and Technology Technical University of Munich 80333 Munich, Germany
DVFace: Spatio-Temporal Dual-Prior Diffusion for Video Face Restoration
Apr 16, 2026Zheng Chen, Bowen Chai, Rongjun Gao +7Video Diffusion Models Image Restoration
Shanghai Jiaotong University · Meituan Inc
SparkVSR: Interactive Video Super-Resolution via Sparse Keyframe Propagation
Mar 17, 2026Jiongze Yu, Xiangbo Gao, Pooja Verlani +4Video Super-Resolution Video Restoration
Texas A&M University · YouTube, Google
LoCAtion: Long-time Collaborative Attention Framework for High Dynamic Range Video Reconstruction
Mar 15, 2026Qianyu Zhang, Bolun Zheng, Lingyu Zhu +3HDR Video Reconstruction Temporal Consistency in Video Restoration
School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China · Department of Computer Science, City University of Hong Kong
Exploring Spatiotemporal Feature Propagation for Video-Level Compressive Spectral Reconstruction: Dataset, Model and Benchmark
Feb 28, 2026Lijing Cai, Zhan Shi, Chenglong Huang +6Temporal Consistency in Video Restoration Hyperspectral Image Reconstruction
InstantViR: Real-Time Video Inverse Problem Solver with Distilled Diffusion Prior
Nov 18, 2025Weimin Bai, Suzhe Xu, Yiwei Ren +4Diffusion-Based Inverse Problems Video Diffusion Models
Peking University · Huaqiao University · Kuaishou Technology

Oct 27, 2026J/K move · Enter open · S save

Taming Noise Initialization for Zero-shot Video Restoration with Image Diffusion Priors

Chong Wang, Zixuan Fu, Hao Cheng, Siyuan Yang+2

School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore · School of Artificial Intelligence, Hebei University of Technology, Tianjin, China · Division of Robotics, Perception and Learning, KTH Royal Institute of Technology, Stockholm, Sweden+1

Temporal Consistency in Video Restoration Video Restoration Diffusion Models

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Recent advances in diffusion models have achieved remarkable success in restoring high-quality images in a zero-shot manner. Unfortunately, extending this success to video restoration is challenging due to the substantial computational resources required to pre-train video diffusion models. A rising trend seeks to address video restoration by utilizing a pre-trained image diffusion model, initiating restoration from either frame-wise independent or identical Gaussian noise. Yet, these approaches often fall short, as such simple noise initiations fail to capture and utilize the inherent temporal correlations within degraded video frames. In this work, we propose taming noise initialization for zero-shot video restoration, which preserves the intrinsic temporal correlations by generating initial noises directly using DDIM inversion on the corrupted video frames themselves. Building on this, we introduce an adaptive noise blending strategy that suppresses degradation patterns encoded during DDIM inversion while gradually steering the noise toward a Gaussian distribution. To further emphasize temporal consistency, we propose measurement-guided trajectory attention to better align features across frames. Extensive experiments on multiple video restoration tasks demonstrate that our method outperforms existing zero-shot approaches, consistently achieving superior results on the DAVIS, REDS4, and Set8 datasets.