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Conference Paper Complex Motion-aware Splatting for Video Frame Interpolation
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Authors
Minho Park, Yuseok Bae
Issue Date
2023-10
Citation
International Conference on Information and Communication Technology Convergence (ICTC) 2023, pp.1872-1876
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICTC58733.2023.10393566
Abstract
Video frame interpolation, a crucial component of computer vision, synthesizes additional frames to enhance the frame rate of a video, leading to improved performance with minimal additional cost. Despite recent advancements with deep learning and convolutional neural networks (CNNs), it still remains a challenge to generate precise intermediate frames, especially when complex and fast motions are involved. This paper presents a novel deep learning-based framework for video frame interpolation that incorporates a complex motion detection module and proposes a complex motion-aware splatting (CMS) method. We employ a forward warping approach that uses a complex motion map as a weight map in splatting. The framework further leverages a module that embeds temporal and spatial information from the frame sequence to acquire motion information. The effectiveness of our proposed model is demonstrated through qualitative and quantitative results on a public dataset.
KSP Keywords
Computer Vision(CV), Convolution neural network(CNN), Forward warping, Improved performance, Learning-based, Motion detection, Motion information, Proposed model, Public Datasets, Video frame interpolation, Weight map