A training framework that uses monocular depth estimates, diffusion inpainting, pseudo-labels and a DINOv2-based encoder to improve zero-shot stereo matching accuracy.
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Boosting Zero-shot Stereo Matching using Large-scale Mixed Images Sources in the Real World
A training framework that uses monocular depth estimates, diffusion inpainting, pseudo-labels and a DINOv2-based encoder to improve zero-shot stereo matching accuracy.