Properties of a Variational Model for Video Inpainting
Sign Up to like & getrecommendations! Published in 2019 at "Networks and Spatial Economics"
DOI: 10.1007/s11067-019-09459-4
Abstract: We consider a variational model analyzed in March and Riey (Inverse Probl Imag 11(6): 997–1025, 2017) for simultaneous video inpainting and motion estimation. The model has applications in the field of recovery of missing data… read more here.
Keywords: video; video inpainting; video data; variational model ... See more keywords
Structure-Guided Deep Video Inpainting
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DOI: 10.1109/tcsvt.2020.3034422
Abstract: A fundamental challenge in video inpainting is the difficulty of generating video contents with fine details, while keeping spatio-temporal coherence in the missing region. Recent studies focus on synthesizing temporally smooth pixels by exploiting the… read more here.
Keywords: video; coherence; inpainting results; structure guided ... See more keywords
Recurrent Temporal Aggregation Framework for Deep Video Inpainting
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DOI: 10.1109/tpami.2019.2958083
Abstract: Video inpainting aims to fill in spatio-temporal holes in videos with plausible content. Despite tremendous progress on deep learning-based inpainting of a single image, it is still challenging to extend these methods to video domain… read more here.
Keywords: video; deep video; recurrent temporal; video inpainting ... See more keywords
Learning a spatial-temporal texture transformer network for video inpainting
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Neurorobotics"
DOI: 10.3389/fnbot.2022.1002453
Abstract: We study video inpainting, which aims to recover realistic textures from damaged frames. Recent progress has been made by taking other frames as references so that relevant textures can be transferred to damaged frames. However,… read more here.
Keywords: texture transformer; temporal texture; transformer network; video inpainting ... See more keywords