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Global context and confidence-guided refinement can unlock state-of-the-art optical flow estimation, even in challenging scenarios with large displacements and occlusions.
Stop hand-labeling real-world videos: a meta-model can learn to verify tracker outputs and generate high-quality pseudo-labels for fine-tuning, achieving SOTA with less data.
