VTinker: Guided Flow Upsampling and Texture Mapping for High-Resolution Video Frame Interpolation
Chenyang Wu, Jiayi Fu, Chun-Le Guo, Shuhao Han, Chongyi Li

TL;DR
VTinker introduces guided flow upsampling and texture mapping to improve high-resolution video frame interpolation, effectively reducing artifacts and enhancing detail preservation compared to existing methods.
Contribution
The paper presents a novel VFI pipeline with guided flow upsampling and texture mapping, addressing low-resolution flow inaccuracies and detail loss in high-resolution frame interpolation.
Findings
Achieves state-of-the-art performance on VFI benchmarks.
Reduces ghosting and discontinuities in interpolated frames.
Improves flow edge clarity and detail preservation.
Abstract
Due to large pixel movement and high computational cost, estimating the motion of high-resolution frames is challenging. Thus, most flow-based Video Frame Interpolation (VFI) methods first predict bidirectional flows at low resolution and then use high-magnification upsampling (e.g., bilinear) to obtain the high-resolution ones. However, this kind of upsampling strategy may cause blur or mosaic at the flows' edges. Additionally, the motion of fine pixels at high resolution cannot be adequately captured in motion estimation at low resolution, which leads to the misalignment of task-oriented flows. With such inaccurate flows, input frames are warped and combined pixel-by-pixel, resulting in ghosting and discontinuities in the interpolated frame. In this study, we propose a novel VFI pipeline, VTinker, which consists of two core components: guided flow upsampling (GFU) and Texture Mapping.…
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Taxonomy
TopicsAdvanced Image Processing Techniques · Advanced Vision and Imaging · Video Coding and Compression Technologies
