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Found 4 papers, 1 papers with code
Revisiting Learning-based Video Motion Magnification for Real-time Processing
Video motion magnification is a technique to capture and amplify subtle motion in a video that is invisible to the naked eye.
Learning-based Axial Video Motion Magnification
In this work, we focus on improving legibility by proposing a new concept, axial motion magnification, which magnifies decomposed motions along the user-specified direction.
The Devil in the Details: Simple and Effective Optical Flow Synthetic Data Generation
Recent work on dense optical flow has shown significant progress, primarily in a supervised learning manner requiring a large amount of labeled data.
DFlow: Learning to Synthesize Better Optical Flow Datasets via a Differentiable Pipeline
Comprehensive studies of synthetic optical flow datasets have attempted to reveal what properties lead to accuracy improvement in learning-based optical flow estimation.
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