ZoeDepth: Better Depth from a Single Photo for Any Scene
Imagine your phone guessing how far things are in a photo, both near and far, accurately.
That's what ZoeDepth does by mixing two ways of learning depth: one that cares about scale and one that cares about relative shape.
The system learns from many pictures, then it fine-tunes to keep real-world size, so results look right in both rooms and streets.
A smart part inside picks which tiny specialist to use for each image, so every photo gets the best treatment.
The model learned on lots of different datasets, so it generalizes well and works on new places it never saw before.
People saw much better depth, even without extra training, and it holds up across indoor and outdoor shots.
This makes apps that add effects, measure space, or help robots more reliable.
It’s a simple idea with big impact: combine strengths, keep real size, and let the model choose for each picture.
The code and models are shared online for others to try, and many developers already testing it with good results.
single image metric depth
Read article comprehensive review in Paperium.net:
ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth
🤖 This analysis and review was primarily generated and structured by an AI . The content is provided for informational and quick-review purposes.
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