Depth Anything —A Foundation Model for Monocular Depth Estimation | by Sascha Kirch

Depth Anything —A Foundation Model for Monocular Depth Estimation | by Sascha Kirch | Mar, 2024

Last updated: 2024/03/21 at 12:59 AM

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Paper: Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data by Lihe Yang, Bingyi Kang, Zilong Huang, Xiaogang Xu, Jiashi Feng, Hengshuang Zhao onathan Ho, Ajay Jain, Pieter Abbeel, 19 Jan. 2024

Code: https://github.com/LiheYoung/Depth-Anything

Project Page: https://depth-anything.github.io/

Conference: CVPR2024

Category: foundation models, monocular depth estimation

Other Walkthroughs: [BYOL], [CLIP], [GLIP], [SAM], [DINO]

Context & Background
Method
Qualitative Results
Experiments & Ablations
Further Readings & Resources

Why is depth such an important modality and why using deep learning for it?

Joint illustration of image and depthmap showing an orange bicycle by Sascha Kirch — Fig.1: Image and corresponding depth map. Image by Sascha Kirch and Depth Map created with Depth Anything Hugging Face Demo.

Put simply: to navigate through 3D space, one must need to know where all the stuff is and at which distance. Classical applications include collision avoidance, drivable space detection, placing objects into a virtual or augmented reality, creating 3D objects, navigating a robot to grab an object and many…