SOTAVerified

BiFormer: Learning Bilateral Motion Estimation via Bilateral Transformer for 4K Video Frame Interpolation

2023-04-05CVPR 2023Code Available1· sign in to hype

Junheum Park, Jintae Kim, Chang-Su Kim

Code Available — Be the first to reproduce this paper.

Reproduce

Code

Abstract

A novel 4K video frame interpolator based on bilateral transformer (BiFormer) is proposed in this paper, which performs three steps: global motion estimation, local motion refinement, and frame synthesis. First, in global motion estimation, we predict symmetric bilateral motion fields at a coarse scale. To this end, we propose BiFormer, the first transformer-based bilateral motion estimator. Second, we refine the global motion fields efficiently using blockwise bilateral cost volumes (BBCVs). Third, we warp the input frames using the refined motion fields and blend them to synthesize an intermediate frame. Extensive experiments demonstrate that the proposed BiFormer algorithm achieves excellent interpolation performance on 4K datasets. The source codes are available at https://github.com/JunHeum/BiFormer.

Tasks

Benchmark Results

DatasetModelMetricClaimedVerifiedStatus
X4K1000FPSBiFormerPSNR31.32Unverified

Reproductions