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Deep Video Harmonization by Improving Spatial-temporal Consistency

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Video harmonization is an important step in video editing to achieve visual consistency by adjusting foreground appear-ances in both spatial and temporal dimensions.Previous methods always only harmonize on a single scale or ignore the inaccuracy of flow estimation,which leads to limited harmonization performance.In this work,we propose a novel architecture for video harmoniza-tion by making full use of spatiotemporal features and yield temporally consistent harmonized results.We introduce multiscale harmon-ization by using nonlocal similarity on each scale to make the foreground more consistent with the background.We also propose a fore-ground temporal aggregator to dynamically aggregate neighboring frames at the feature level to alleviate the effect of inaccurate estim-ated flow and ensure temporal consistency.The experimental results demonstrate the superiority of our method over other state-of-the-art methods in both quantitative and visual comparisons.

Harmonizationtemporal consistencyvideo editingvideo compositionnonlocal similarity

Xiuwen Chen、Li Fang、Long Ye、Qin Zhang

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Key Laboratory of Media Audio and Video Ministry of Education,Communication University of China,Beijing 100024,China

National Natural Science Foundation of ChinaFundamental Research Funds for the Central Universities,ChinaFundamental Research Funds for the Central Universities,China

62001432CUC18LG024CUC22JG001

2024

10.1007/s11633-023-1447-3

机器智能研究(英文)
中国科学院自动化所

机器智能研究(英文)

CSTPCDEI
影响因子：0.49
ISSN：2731-538X
年,卷(期)：2024.21(1)
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