Feature pyramid warping for video frame interpolation
AssigneePortland State University
InventorsFeng LIU, Simon NIKLAUS
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AssigneePortland State University
InventorsFeng LIU, Simon NIKLAUS
Estimating the term…
Methods, systems, and storage media are described for motion estimation in video frame interpolation. Disclosed embodiments use feature pyramids as image representations for motion estimation and seamlessly integrates them into a deep neural network for frame interpolation. A feature pyramid is extracted for each of two input frames. These feature pyramids are wrapped together with the input frames to the target temporal position according to the inter-frame motion estimated via optical flow. A frame synthesis network is used to predict interpolation results from the pre-warped feature pyramids and input frames. The feature pyramid extractor and the frame synthesis network are jointly trained for the task of frame interpolation. An extensive quantitative and qualitative evaluation demonstrates that the described embodiments utilizing feature pyramids enables robust, high-quality video frame interpolation. Other embodiments may be described and/or claimed.
An integrated circuit (IC) package configured to operate a frame interpolation neural network (FINN), the IC comprising:
One or more non-transitory computer-readable media (NTCRM) comprising instructions of a frame interpolation neural network (FINN), wherein execution of the instructions by one or more processors is to cause the one or more processors to:
A computing system comprising:
Dependencies are inferred from the claim text.