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All at Once: Temporally Adaptive Multi-frame Interpolation with Advanced Motion Modeling

机译:一下子:时间上自适应多帧插值,具有高级运动建模

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Recent advances in high refresh rate displays as well as the increased interest in high rate of slow motion and frame up-conversion fuel the demand for efficient and cost-effective multi-frame video interpolation solutions. To that regard, inserting multiple frames between consecutive video frames are of paramount importance for the consumer electronics industry. State-of-the-art methods are iterative solutions interpolating one frame at the time. They introduce temporal inconsistencies and clearly noticeable visual artifacts. Departing from the state-of-the-art, this work introduces a true multi-frame interpolator. It utilizes a pyramidal style network in the temporal domain to complete the multi-frame interpolation task in one-shot. A novel flow estimation procedure using a relaxed loss function, and an advanced, cubic-based, motion model is also used to further boost interpolation accuracy when complex motion segments are encountered. Results on the Adobe240 dataset show that the proposed method generates visually pleasing, temporally consistent frames, outperforms the current best off-the-shelf method by 1.57dB in PSNR with 8 times smaller model and 7.7 times faster. The proposed method can be easily extended to interpolate a large number of new frames while remaining efficient because of the one-shot mechanism.
机译:最近在高刷新率显示的进展以及高慢速运动的高兴趣和帧上升率的增加燃料对高效且经济高效的多帧视频插值解决方案的需求。为此,在连续视频帧之间插入多个帧对消费电子行业至关重要。最先进的方法是当时内插一帧的迭代解决方案。他们介绍时间不一致,明显明显的视觉伪影。从最先进的情况下,这项工作引入了一个真正的多帧内插器。它利用时间域中的金字塔式样式网络在一次拍摄中完成多帧插值任务。使用缓和损耗功能的新型流程估计程序,以及先进的立方体的运动模型,也用于在遇到复杂的运动段时进一步提升内插精度。结果在Adobe240数据集上表明,所提出的方法在视觉上令人愉悦,时间上一致的帧中产生,优于PSNR中最佳的现成方法,在PSNR中,较小模型8倍,速度快7.7倍。所提出的方法可以很容易地扩展以插入大量新帧,同时由于单次机制而剩余效率。

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