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Thrilled to introduce Video Depth Anything to support Depth Estimation for super-long videos (over 5 minutes). 👉It enjoys all the benefits of #DepthAnything: high-quality, fast, robust, etc. Proj Page:

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Bingyi Kang

1,111 subscribers

25,464 görüntüleme • 1 yıl önce •via X (Twitter)

SanatBilim & TeknolojiEğitim#DepthAnything
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Bingyi Kang profil fotoğrafı
Bingyi Kang1 yıl önce

Arxiv: Code: HuggingFace Demo: Thank again for the generous support of @huggingface @pcuenq @_akhaliq in severing our demo.

Suppybird Kingdom profil fotoğrafı
Suppybird Kingdom1 yıl önce

Thank you. Very useful <3

Jonathan Granskog profil fotoğrafı
Jonathan Granskog1 yıl önce

looks great! congrats!

Aradhye Agarwal profil fotoğrafı
Aradhye Agarwal1 yıl önce

Hi, great work! Could you share the link to the RGB videos?

Leor Cohen profil fotoğrafı
Leor Cohen1 yıl önce

Looks amazing! 🔥

AIサポートで楽しく小説を書こう。NovelShaft profil fotoğrafı
AIサポートで楽しく小説を書こう。NovelShaft1 yıl önce

素晴らしいプロジェクトですね！ビデオの深度推定に興味があります 😊

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Want to use Depth Anything, but need metric depth rather than relative depth? Thrilled to introduce Prompt Depth Anything, a new paradigm for accurate metric depth estimation with up to 4K resolution. 👉Key Message: Depth foundation models like DA have already internalized rich geometric knowledge of the 3D world but lack a proper way to elicit it. Inspired by the success of prompting in LLMs, we propose prompting Depth Anything with metric cues to produce metric depth. This method proves to be very effective when using a low-cost lidar (e.g., iPhone's LiDAR), which is widely available, as prompts. We believe the prompt can generalize to other forms as long as scale information is provided. Prompt Depth Anything offers 1⃣A series of models for iPhone lidars. 2⃣4D reconstruction from monocular videos (captured with iPhone). 3⃣Improved generalization ability for robot manipulation, e.g. Training on cans but generalizing on glasses. 4⃣More detailed depth annotations for the ScanNet++ dataset. The first author is our excellent intern Haotong Lin. Paper: Huggingface: Project Page: Code:

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