TY - GEN
T1 - Asymmetric Bilateral Motion Estimation for Video Frame Interpolation
AU - Park, Junheum
AU - Lee, Chul
AU - Kim, Chang Su
N1 - Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) grants funded by the Korea government (MSIT) (Nos. NRF-2018R1A2B3003896, NRF-2019R1A2C4069806, and NRF-2021R1A4A1031864).
Publisher Copyright:
© 2021 IEEE
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85127784999&partnerID=8YFLogxK
U2 - 10.1109/ICCV48922.2021.01427
DO - 10.1109/ICCV48922.2021.01427
M3 - Conference contribution
AN - SCOPUS:85127784999
T3 - Proceedings of the IEEE International Conference on Computer Vision
SP - 14519
EP - 14528
BT - Proceedings - 2021 IEEE/CVF International Conference on Computer Vision, ICCV 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 18th IEEE/CVF International Conference on Computer Vision, ICCV 2021
Y2 - 11 October 2021 through 17 October 2021
ER -