VQV Signal
SNM-VFI is a training-free framework for video frame interpolation that uses pre-trained optical flow and video diffusion models to generate motion-controllable intermediate frames. It improves on conventional diffusion-based methods by guiding synthesis with correspondence-aware frames rather than...
SNM-VFI is a training-free framework for video frame interpolation that uses pre-trained optical flow and video diffusion models to generate motion-controllable intermediate frames. It improves on conventional diffusion-based methods by guiding synthesis with correspondence-aware frames rather than...
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We propose Symmetric Nonlinear Motion-guided Generative Video Frame Interpolation (SNM-VFI), a training-free framework for motion-controllable generative video frame interpolation with pre-trained optical flow and video diffusion models. Unlike conventional diffusion-based VFI methods that synthesize intermediate...
This approach enables more accurate and controllable video frame interpolation without the need for additional training, potentially enhancing video editing and generation workflows. It leverages existing models to produce smoother and more coherent intermediate frames.
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