Multi-Scale Warping for Video Frame Interpolation

被引:1
|
作者
Choi, Whan [1 ]
Koh, Yeong Jun [2 ]
Kim, Chang-Su [1 ]
机构
[1] Korea Univ, Sch Elect Engn, Seoul 136701, South Korea
[2] Chungnam Natl Univ, Dept Comp Sci & Engn, Daejeon 34134, South Korea
基金
新加坡国家研究基金会;
关键词
Interpolation; Kernel; Feature extraction; Convolution; Adaptive optics; Streaming media; Optical imaging; Video frame interpolation; convolutional neural network; multi-scale feature; kernel-based approach; deformable convolution; adaptive convolution; MOTION ESTIMATION;
D O I
10.1109/ACCESS.2021.3126593
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A novel video interpolation network to improve the temporal resolutions of video sequences is proposed in this work. We develop a multi-scale warping module to interpolate intermediate frames robustly for both small and large motions. Specifically, the proposed multi-scale warping module deals with large motions between two consecutive frames using coarse-scale features, while estimating detailed local motions by exploring fine-scale features. To this end, it takes multi-scale features from the encoder and estimates kernel weights and offset vectors for each scale. Finally, it synthesizes multi-scale warping frames and combines them to obtain an intermediate frame. Extensive experimental results demonstrate that the proposed algorithm outperforms state-of-the-art video interpolation algorithms on various benchmark datasets.
引用
收藏
页码:150470 / 150479
页数:10
相关论文
共 50 条
  • [1] Multi-scale Intermediate Flow Estimation for Video Frame Interpolation
    Fan, Zehua
    Zhu, Feng
    Li, Lei
    Tan, Xiaoyang
    2022 IEEE 34TH INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE, ICTAI, 2022, : 893 - 900
  • [2] Video frame interpolation via spatial multi-scale modelling
    Qu, Zhe
    Liu, Weijing
    Cui, Lizhen
    Yang, Xiaohui
    IET COMPUTER VISION, 2024, 18 (04) : 458 - 472
  • [3] A Multi-Scale Position Feature Transform Network for Video Frame Interpolation
    Cheng, Xianhang
    Chen, Zhenzhong
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2020, 30 (11) : 3968 - 3981
  • [4] Video Frame Interpolation via Multi-scale Expandable Deformable Convolution
    Zhang, Dengyong
    Huang, Pu
    Ding, Xiangling
    Li, Feng
    Yang, Gaobo
    PROCEEDINGS OF THE 2023 ACM WORKSHOP ON INFORMATION HIDING AND MULTIMEDIA SECURITY, IH&MMSEC 2023, 2023, : 19 - 28
  • [5] Multi-Scale Attention Generative Adversarial Networks for Video Frame Interpolation
    Xiao, Jian
    Bi, Xiaojun
    IEEE ACCESS, 2020, 8 : 94842 - 94851
  • [6] Hybrid Warping Fusion for Video Frame Interpolation
    Li, Yu
    Zhu, Ye
    Li, Ruoteng
    Wang, Xintao
    Luo, Yue
    Shan, Ying
    INTERNATIONAL JOURNAL OF COMPUTER VISION, 2022, 130 (12) : 2980 - 2993
  • [7] Hybrid Warping Fusion for Video Frame Interpolation
    Yu Li
    Ye Zhu
    Ruoteng Li
    Xintao Wang
    Yue Luo
    Ying Shan
    International Journal of Computer Vision, 2022, 130 : 2980 - 2993
  • [8] EMCFN: Edge-based Multi-scale Cross Fusion Network for video frame interpolation
    Wang, Shaowen
    Yang, Xiaohui
    Feng, Zhiquan
    Sun, Jiande
    Liu, Ju
    JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 2024, 103
  • [9] Multi-Scale Coarse-to-Fine Transformer for Frame Interpolation
    Li, Chen
    Song, Li
    Zou, Xueyi
    Guo, Jiaming
    Yan, Youliang
    Zhang, Wenjun
    PROCEEDINGS OF THE 30TH ACM INTERNATIONAL CONFERENCE ON MULTIMEDIA, MM 2022, 2022, : 5201 - 5209
  • [10] An Efficient Multi-Scale Attention Feature Fusion Network for 4K Video Frame Interpolation
    Ning, Xin
    Li, Yuhang
    Feng, Ziwei
    Liu, Jinhua
    Ding, Youdong
    ELECTRONICS, 2024, 13 (06)