DyFN is a lightweight recurrent module that dynamically normalizes latent feature statistics to remove scale-shift drift and achieve state-of-the-art temporal consistency in streaming monocular geometry estimation while updating only 2% of parameters.
Video depth without video models.arXiv preprint arXiv:2411.19189, 2024
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Stabilizing Streaming Video Geometry via Dynamic Feature Normalization
DyFN is a lightweight recurrent module that dynamically normalizes latent feature statistics to remove scale-shift drift and achieve state-of-the-art temporal consistency in streaming monocular geometry estimation while updating only 2% of parameters.