Full papers
Accepted full papers will be published in the official ICPR 2026 Workshop Proceedings in the Lecture Notes in Computer Science (LNCS) series. Must be more than 6 pages.
Computer Vision/CORE Unranked
PAVER 2026
Physics-Aware Video gEneration and Restoration
Aug 26 2026Official conference site Site reachable
The PAVER 2026 workshop, held at ICPR 2026 in Lyon, France, focuses on physics-aware video generation and restoration, bringing together researchers from computer vision, machine learning, and physics-based modeling. It aims to advance realistic video synthesis by integrating physical laws and real-world priors for applications in autonomous driving, medical imaging, surveillance, and immersive technologies.
Key deadlines
Verified September 9, 2026Full paper
June 1, 2026
AoE
Conference timeline
Submission and decisions
Full paperKey deadline
June 1, 2026 · AoE
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Short papers
Short papers (6 pages or fewer) will be presented at the workshop but will not appear in the LNCS proceedings.
Research areas in scope
01
Physics-aware Video Generation
Integrating physical laws, fluid dynamics, and rigid-body motion into generative modelsTemporal consistency in video generation: Addressing flickering, motion coherence, and long-term dynamicsPhysics-aware video generation: A survey of first-principles and common-sense approaches
02
Video Restoration and Enhancement
Video super-resolution and enhancement: Transforming low-quality video (SD-to-HD, SDR-to-HDR) while preserving physical realismGenerative AI for video restoration: Applications of diffusion models, GANs, and transformersVideo artifact removal and enhancement: Denoising, deblurring, inpainting, and artifact removal
03
Data and Learning Methods
Synthetic data generation for video restoration: Using physics-based rendering and generative modelsDomain adaptation and cross-modal learning: Leveraging multi-modal information for robust video synthesisSelf-supervised and unsupervised learning for video restoration: Training with minimal labeled dataEfficient video generation and restoration: Optimizing for real-time applications and edge computing
04
Evaluation and Benchmarking
Benchmarking and evaluation metrics: Novel full-reference, reduced-reference, and no-reference metricsPVIR-Bench: A Physics-Aware Benchmark for Video Instance Removal
05
Applications
Application-driven video enhancement: For medical, autonomous driving, surveillance, and creative industries
06
Ethics and Impact
Ethical considerations and societal impact: Addressing biases, misinformation risks, and responsible AI use
Policies worth checking twice
- Submissions must be original and not under review elsewhere.
- Papers must not exceed 15 pages, including references.
- An additional fee of €150 per extra page applies if a paper exceeds 15 pages.
- Only full papers (more than 6 pages) will be published in the LNCS proceedings.
- Papers will undergo peer review by the program committee.
- Submissions must follow the LNCS formatting guidelines provided on the ICPR 2026 website.
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified September 9, 2026