Papers › BiM-VFI: directional Motion Field-Guided Frame Interpolation for Video with Non-uniform Motions

BiM-VFI: directional Motion Field-Guided Frame Interpolation for Video with Non-uniform Motions

16 Dec 2024arXiv:2412.11365archive 2025-07-28

Wonyong Seo, Jihyong Oh, Munchurl Kim

Existing Video Frame interpolation (VFI) models tend to suffer from time-to-location ambiguity when trained with video of non-uniform motions, such as accelerating, decelerating, and changing directions, which often yield blurred interpolated frames. In this paper, we propose (i) a novel motion description map, Bidirectional Motion field (BiM), to effectively describe non-uniform motions; (ii) a BiM-guided Flow Net (BiMFN) with Content-Aware Upsampling Network (CAUN) for precise optical flow estimation; and (iii) Knowledge Distillation for VFI-centric Flow supervision (KDVCF) to supervise the motion estimation of VFI model with VFI-centric teacher flows. The proposed VFI is called a Bidirectional Motion field-guided VFI (BiM-VFI) model. Extensive experiments show that our BiM-VFI model significantly surpasses the recent state-of-the-art VFI methods by 26% and 45% improvements in LPIPS and STLPIPS respectively, yielding interpolated frames with much fewer blurs at arbitrary time instances.

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KAIST-VICLab/BiM-VFI mentioned on GitHubpytorch report

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Tasks

Knowledge DistillationMotion EstimationOptical Flow EstimationVideo Frame Interpolation

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Knowledge Distillation

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