Depth Anything V2 is trained from 595K synthetic labeled images and 62M+ real unlabeled images, providing the most capable monocular depth estimation (MDE) model with the following features: - more fine-grained details than Depth Anything V1 - more robust than Depth Anything V1 and SD-based models (e.g., Marigold, Geowizard) - more efficient (10x faster) and more lightweight than SD-based models - impressive fine-tuned performance with our pre-trained models Download the model first and put it under the `checkpoints` directory. ```bibtex @article{depth_anything_v2, title={Depth Anything V2}, author={Yang, Lihe and Kang, Bingyi and Huang, Zilong and Zhao, Zhen and Xu, Xiaogang and Feng, Jiashi and Zhao, Hengshuang}, journal={arXiv:2406.09414}, year={2024} }
_**Wenbo Hu 1* † , Xiangjun Gao 2* , Xiaoyu Li 1* † , Sijie Zhao 1 , Xiaodong Cun 1 , Yong Zhang 1 , Long Quan 2 , Ying Shan 3, 1 **_ If you find DepthCrafter useful, please help ⭐ the [Github Repo] , which is important to Open-Source projects. Thanks! 🤗 DepthCrafter can generate temporally consistent long depth sequences with fine-grained details for open-world videos, without requiring additional information such as camera poses or optical flow.
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