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Coherent Online Video Style Transfer
[article]
2017
arXiv
pre-print
Training a feed-forward network for fast neural style transfer of images is proven to be successful. However, the naive extension to process video frame by frame is prone to producing flickering results. We propose the first end-to-end network for online video style transfer, which generates temporally coherent stylized video sequences in near real-time. Two key ideas include an efficient network by incorporating short-term coherence, and propagating short-term coherence to long-term, which
arXiv:1703.09211v2
fatcat:jjmqeuruenfmhmu55krjcrs7ie