Video Frame Interpolation On Msu Video Frame

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이 벤치마크에서 각 모델의 성능 결과

						Paper Title
EMA-VFI	0.022	0.965	29.89	0.953	71.71	Extracting Motion and Appearance via Inter-Frame Attention for Efficient Video Frame Interpolation
UPR-Net LARGE	0.025	0.962	29.73	0.951	71.34	A Unified Pyramid Recurrent Network for Video Frame Interpolation
DQBC	0.021	0.961	29.45	0.949	72.12	Video Frame Interpolation with Densely Queried Bilateral Correlation
EBME-H	0.024	0.958	28.77	0.931	68.20	Enhanced Bi-directional Motion Estimation for Video Frame Interpolation
EBME	0.028	0.957	28.56	0.928	69.37	Enhanced Bi-directional Motion Estimation for Video Frame Interpolation
VFIformer	0.044	0.942	28.34	0.917	68.87	Video Frame Interpolation with Transformer
FILM	0.033	0.948	28.11	0.928	68.68	FILM: Frame Interpolation for Large Motion
IFRNet_large	0.037	0.943	28.04	0.921	66.98	IFRNet: Intermediate Feature Refine Network for Efficient Frame Interpolation
CURE	0.029	0.946	28.01	0.920	67.07	Learning Cross-Video Neural Representations for High-Quality Frame Interpolation
ABME	0.039	0.945	27.99	0.919	68.10	Asymmetric Bilateral Motion Estimation for Video Frame Interpolation
XVFI (S_{tst}=5)	0.049	0.955	27.86	0.921	67.25	XVFI: eXtreme Video Frame Interpolation
IFRNet_base	0.048	0.932	27.67	0.909	64.16	IFRNet: Intermediate Feature Refine Network for Efficient Frame Interpolation
IFRNet_small	0.049	0.931	27.45	0.908	63.43	IFRNet: Intermediate Feature Refine Network for Efficient Frame Interpolation
XVFI (S_{tst}=3)	0.061	0.933	27.35	0.913	63.47	XVFI: eXtreme Video Frame Interpolation
RIFE	0.039	0.939	27.15	0.914	66.33	Real-Time Intermediate Flow Estimation for Video Frame Interpolation
CDFI	0.051	0.926	26.99	0.908	61.72	CDFI: Compression-Driven Network Design for Frame Interpolation
Super-SloMo	0.068	0.924	26.69	0.904	61.35	Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation
SepConv-L1	-	-	26.36	-	-	Video Frame Interpolation via Adaptive Separable Convolution
RRIN	0.072	0.902	25.76	0.893	59.82	Video Frame Interpolation via Residue Refinement
AdaCoF_f	0.058	0.913	24.99	0.903	60.19	AdaCoF: Adaptive Collaboration of Flows for Video Frame Interpolation

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Video Frame Interpolation On Msu Video Frame

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