ZoeDepth (fine tuned on NYU and KITTI) ZoeDepth model fine tuned on the NYU and KITTI datasets. It was introduced in the paper ZoeDepth: Zero shot Transfer by Combining Relative and Metric Depth by Shariq et al. and first released in this repository. ZoeDepth extends the DPT framework for metric (also called absolute) depth estimation, obtaining state of the art results. Disclaimer: The team releasing ZoeDepth did not write a model card for this model so this model card has been written by the Hugging Face team. Model description ZoeDepth adapts DPT, a model for relative depth estimation, for so called metric (also called absolute) depth estimation. This means that the model is able to estimate depth in actual metric values. ZoeDepth architecture. Taken from the original paper. Intended uses & limitations You can use the raw model for tasks like zero shot monocular depth estimation. See the model hub to look for other versions on a task that interests you. How to use The easiest is to leverage the pipeline API which abstracts away the complexity for the user: For more code examples, we refer to the documentation. BibTeX entry and citation info
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