Video Frame Interpolation On Vimeo90K

PSNR

Results

Performance results of various models on this benchmark

		Paper Title
MA-CSPA	36.76	Exploring Motion Ambiguity and Alignment for High-Quality Video Frame Interpolation
EMA-VFI	36.64	Extracting Motion and Appearance via Inter-Frame Attention for Efficient Video Frame Interpolation
DQBC	36.57	Video Frame Interpolation with Densely Queried Bilateral Correlation
UPR-Net LARGE	36.42	A Unified Pyramid Recurrent Network for Video Frame Interpolation
IFRNet	36.20	IFRNet: Intermediate Feature Refine Network for Efficient Frame Interpolation
EBME-H*	36.19	Enhanced Bi-directional Motion Estimation for Video Frame Interpolation
ABME	36.18	Asymmetric Bilateral Motion Estimation for Video Frame Interpolation
SoftSplat	36.10	Softmax Splatting for Video Frame Interpolation
FILM	36.06	FILM: Frame Interpolation for Large Motion
NCM-Base	35.88	Neighbor Correspondence Matching for Flow-based Video Frame Synthesis
CURE	35.73	Learning Cross-Video Neural Representations for High-Quality Frame Interpolation
M2M-PWC	35.4	Many-to-many Splatting for Efficient Video Frame Interpolation
RRIN	35.22	Video Frame Interpolation via Residue Refinement
CDFI	35.17	CDFI: Compression-Driven Network Design for Frame Interpolation
XVFI	35.07	XVFI: eXtreme Video Frame Interpolation
BMBC	35.01	BMBC:Bilateral Motion Estimation with Bilateral Cost Volume for Video Interpolation
ECMNet	34.95	Enhanced Correlation Matching based Video Frame Interpolation
DAIN	34.71	Depth-Aware Video Frame Interpolation
DAIN	34.71	Depth-Aware Video Frame Interpolation
FRUCnet	34.65	-

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