Exploiting optical flow guidance for parallel structure video inpainting

Yong Zhang; JiaMing Wu

doi:10.1117/12.2687358

21 July 2023 Exploiting optical flow guidance for parallel structure video inpainting

Yong Zhang, JiaMing Wu

Proceedings Volume 12717, 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023); 127172H (2023) https://doi.org/10.1117/12.2687358
Event: 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023), 2023, Wuhan, China

Abstract

To solve the problem of video repair, we propose a new optical flow guidance solution that uses parallel structured convolution and attention networks to jointly infer video missing regions. In the network, a parallel structural model based on convolution and attention networks guided by optical flow is used to extract feature information to integrate the spatial and temporal context of video frames. This method integrates information between the target frame and the reference frame. To enhance feature learning capabilities using convolution and attention mechanisms, the feature fusion module fuses local and global features in an interactive manner, maximizing the retention of local and global representations. Our model produces visually satisfactory and time consistent results, while demonstrating on two benchmark datasets that our method outperforms the most advanced methods in terms of quantity and user research.

Citation Download Citation

Yong Zhang and JiaMing Wu "Exploiting optical flow guidance for parallel structure video inpainting", Proc. SPIE 12717, 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023), 127172H (21 July 2023); https://doi.org/10.1117/12.2687358

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KEYWORDS

Video

Optical flow

Feature extraction

Network architectures

Education and training

Optical networks

Video coding

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