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3 months ago

Asymmetric Bilateral Motion Estimation for Video Frame Interpolation

Junheum Park Chul Lee Chang-Su Kim

Asymmetric Bilateral Motion Estimation for Video Frame Interpolation

Abstract

We propose a novel video frame interpolation algorithm based on asymmetric bilateral motion estimation (ABME), which synthesizes an intermediate frame between two input frames. First, we predict symmetric bilateral motion fields to interpolate an anchor frame. Second, we estimate asymmetric bilateral motions fields from the anchor frame to the input frames. Third, we use the asymmetric fields to warp the input frames backward and reconstruct the intermediate frame. Last, to refine the intermediate frame, we develop a new synthesis network that generates a set of dynamic filters and a residual frame using local and global information. Experimental results show that the proposed algorithm achieves excellent performance on various datasets. The source codes and pretrained models are available at https://github.com/JunHeum/ABME.

Code Repositories

junheum/abme
Official
pytorch
Mentioned in GitHub

Benchmarks

BenchmarkMethodologyMetrics
video-frame-interpolation-on-msu-video-frameABME
LPIPS: 0.039
MS-SSIM: 0.945
PSNR: 27.99
SSIM: 0.919
VMAF: 68.10
video-frame-interpolation-on-ucf101-1ABME
PSNR: 35.38
SSIM: 0.9698
video-frame-interpolation-on-vimeo90kABME
PSNR: 36.18
SSIM: 0.9805
video-frame-interpolation-on-x4k1000fpsABME
PSNR: 30.16
SSIM: 0.8793

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Asymmetric Bilateral Motion Estimation for Video Frame Interpolation | Papers | HyperAI