# Depth Anything V2 Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/depth-anything-v2
> Markdown URL: https://aitinkerers.org/technologies/depth-anything-v2.md
> Technology record last updated: 2026-04-04T21:33:45Z
> Generated: 2026-10-25T09:07:28Z

A foundation model for monocular depth estimation (MDE): it delivers fine-grained, robust depth maps from a single image, operating 10x faster than SD-based models.

Depth Anything V2 is the next-generation foundation model for monocular depth estimation (MDE). It achieves superior, fine-grained depth predictions by leveraging a teacher-student distillation framework: a large teacher model is trained on 595K synthetic images, then generates pseudo-labels for over 62M unlabeled real-world images. This approach ensures greater robustness and detail than V1. Critically, it offers models from 25M to 1.3B parameters and boasts over 10x faster inference speed compared to models built on Stable Diffusion (SD), making it a highly efficient solution for real-time applications.

- Official technology site: https://github.com/DepthAnything/Depth-Anything-V2
- Public AI Tinkerers demos and talks: 1
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Civil engineer in your pocket](https://nyc.aitinkerers.org/talks/rsvp_EeO7Jk3AhL4)

- Event context: AI Tinkerers August Demo Day ft. Auth0 and Comet. Demo what you've built! — 2025-08-26 — New York City
- Public talk page: https://nyc.aitinkerers.org/talks/rsvp_EeO7Jk3AhL4

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