Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
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Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data
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paper page: 
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paper page: 
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data (2401.10891)
https://huggingface.co/papers/2401.10891
2401.10891
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https://huggingface.co/papers/2401.10891
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demo: 
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demo: 
https://huggingface.co/spaces/LiheYoung/Depth-Anything
LiheYoung/Depth-Anything
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https://huggingface.co/spaces/LiheYoung/Depth-Anything
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Depth Anything is trained on 1.5M labeled images and 62M+ unlabeled images jointly, providing the most capable Monocular Depth Estimation (MDE) foundation models with the following features:
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Depth Anything is trained on 1.5M labeled images and 62M+ unlabeled images jointly, providing the most capable Monocular Depth Estimation (MDE) foundation models with the following features:
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zero-shot relative depth estimation, better than MiDaS v3.1 (BEiTL-512)
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zero-shot relative depth estimation, better than MiDaS v3.1 (BEiTL-512)
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zero-shot metric depth estimation, better than ZoeDepth
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zero-shot metric depth estimation, better than ZoeDepth
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optimal in-domain fine-tuning and evaluation on NYUv2 and KITTI
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optimal in-domain fine-tuning and evaluation on NYUv2 and KITTI
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Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

paper page: https://huggingface.co/papers/2401.10891
demo: https://huggingface.co/spaces/LiheYoung/Depth-Anything

Depth Anything is trained on 1.5M labeled images and 62M+ unlabeled images jointly, providing the most capable Monocular Depth Estimation (MDE) foundation models with the following features:

zero-shot relative depth estimation, better than MiDaS v3.1 (BEiTL-512)

zero-shot metric depth estimation, better than ZoeDepth

optimal in-domain fine-tuning and evaluation on NYUv2 and KITTI

👍
Norod78 jgitsolutions clem Chunte alazro victor samusenps XaevrM NeuralNovel Kutches
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s3nh NeuralNovel clem Triyansha