Video yükleniyor...

Video Yüklenemedi

Bu video yüklenirken bir sorun oluştu. Bu geçici bir ağ sorunundan kaynaklanıyor olabilir veya video kullanılamıyor olabilir.

Ana Sayfaya Dön

AnyDepth Depth Estimation Made Easy

AK

532,415 subscribers

14,837 görüntüleme • 9 ay önce •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

1 Yorum

AK profil fotoğrafı

AK9 ay önce

discuss:

Benzer Videolar

DVD Deterministic Video Depth Estimation with Generative Priors paper:

DVD Deterministic Video Depth Estimation with Generative Priors paper:

AK

62,895 görüntüleme • 7 ay önce

XR Animator EARLY ACCESS release (v0.40.1) ・💡Add "Z smoothing" option for hip depth estimation ・Update depth estimation AI models ・Update electron (v43.1.1) ・Other bug fixes #XRAnimator Details below🧵

XR Animator EARLY ACCESS release (v0.40.1) ・💡Add "Z smoothing" option for hip depth estimation ・Update depth estimation AI models ・Update electron (v43.1.1) ・Other bug fixes #XRAnimator Details below🧵

Butz Yung

13,463 görüntüleme • 3 ay önce

TikTok presents Depth Anything Unleashing the Power of Large-Scale Unlabeled Data paper page: demo: 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

TikTok presents Depth Anything Unleashing the Power of Large-Scale Unlabeled Data paper page: demo: 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

AK

600,399 görüntüleme • 2 yıl önce

Monocular depth estimation is “impossible” because one image can’t measure depth geometrically. Our iDisc #CVPR2023 can group pixels w/o supervision and learn depth inductive bias on groups. We get LiDAR-like (but denser) depth from single images! More:

Monocular depth estimation is “impossible” because one image can’t measure depth geometrically. Our iDisc #CVPR2023 can group pixels w/o supervision and learn depth inductive bias on groups. We get LiDAR-like (but denser) depth from single images! More:

Fisher Yu

52,430 görüntüleme • 3 yıl önce

InfiniDepth: Fine-grained depth estimation at any resolution; models depth as a neural implicit field instead of a grid; - tops DepthAnything; - recovers sharp details w/ a lightweight 15M decoder.

InfiniDepth: Fine-grained depth estimation at any resolution; models depth as a neural implicit field instead of a grid; - tops DepthAnything; - recovers sharp details w/ a lightweight 15M decoder.

Wildminder

59,393 görüntüleme • 9 ay önce

Depth Anything V2 This work presents Depth Anything V2. Without pursuing fancy techniques, we aim to reveal crucial findings to pave the way towards building a powerful monocular depth estimation model. Notably, compared with V1, this version produces much finer and more

Depth Anything V2 This work presents Depth Anything V2. Without pursuing fancy techniques, we aim to reveal crucial findings to pave the way towards building a powerful monocular depth estimation model. Notably, compared with V1, this version produces much finer and more

AK

114,537 görüntüleme • 2 yıl önce

Check-out 📢DUSt3R📢 - a new 3D reconstruction model that works with no prior info on camera calibration nor viewpoint poses! Outperforms SoA monocular & multiview depth estimation & relative pose estimation. Paper, demo, videos (& soon code!) available

Check-out 📢DUSt3R📢 - a new 3D reconstruction model that works with no prior info on camera calibration nor viewpoint poses! Outperforms SoA monocular & multiview depth estimation & relative pose estimation. Paper, demo, videos (& soon code!) available

NAVER LABS Europe

17,160 görüntüleme • 2 yıl önce

Learning Temporally Consistent Video Depth from Video Diffusion Priors This work addresses the challenge of video depth estimation, which expects not only per-frame accuracy but, more importantly, cross-frame consistency. Instead of directly

Learning Temporally Consistent Video Depth from Video Diffusion Priors This work addresses the challenge of video depth estimation, which expects not only per-frame accuracy but, more importantly, cross-frame consistency. Instead of directly

AK

81,666 görüntüleme • 2 yıl önce

Example of what AI generation can do in practice currently, from initial image (which is also generated) to a very detailed printable model, the level of detail mostly made possible with the Marigold depth estimation. #ai #3dprinting #dragon #technology

Example of what AI generation can do in practice currently, from initial image (which is also generated) to a very detailed printable model, the level of detail mostly made possible with the Marigold depth estimation. #ai #3dprinting #dragon #technology

Jukka Seppänen

13,934 görüntüleme • 2 yıl önce

Early test run with freshly added depth estimation — Mixed Reality + Diffusion prototype to explore concepts, styles, and moods. #MixedReality #MR #AI #StableDiffusion #Quest3

Early test run with freshly added depth estimation — Mixed Reality + Diffusion prototype to explore concepts, styles, and moods. #MixedReality #MR #AI #StableDiffusion #Quest3

Hugues Bruyère

13,054 görüntüleme • 1 yıl önce

How can lightweight drones without depth cameras navigate using monocular images? Check out our paper at ISER 2023! MonoNav: MAV Navigation via Monocular Depth Estimation and Reconstruction arXiv: website: Work led by Nate Simon

How can lightweight drones without depth cameras navigate using monocular images? Check out our paper at ISER 2023! MonoNav: MAV Navigation via Monocular Depth Estimation and Reconstruction arXiv: website: Work led by Nate Simon

Anirudha Majumdar

27,726 görüntüleme • 2 yıl önce

Presenting MonoNeRF at #ICML2023 We train a generalizable NeRF from: ✅Large-scale monocular videos instead of one scene ✅No GT camera poses.📷🚫 Without per-scene optimization, the model can do view synthesis, depth estimation, camera pose estimation.

Presenting MonoNeRF at #ICML2023 We train a generalizable NeRF from: ✅Large-scale monocular videos instead of one scene ✅No GT camera poses.📷🚫 Without per-scene optimization, the model can do view synthesis, depth estimation, camera pose estimation.

Xiaolong Wang

36,588 görüntüleme • 3 yıl önce

After a year of team work, we're thrilled to introduce Depth Anything 3 (DA3)! 🚀 Aiming for human-like spatial perception, DA3 extends monocular depth estimation to any-view scenarios, including single images, multi-view images, and video. In pursuit of minimal modeling, DA3 reveals two key insights: 💎 A plain transformer (e.g., vanilla DINO) is enough. No specialized architecture. ✨ A single depth-ray representation is enough. No complex 3D tasks. Three series of models have been released: the main DA3 series, a monocular metric estimation series, and a monocular depth estimation series. The core team members, aside from me: Haotong Lin, Sili Chen, Jun Hao Liew, Donny Y. Chen. 👇(1/n) #DepthAnything3

After a year of team work, we're thrilled to introduce Depth Anything 3 (DA3)! 🚀 Aiming for human-like spatial perception, DA3 extends monocular depth estimation to any-view scenarios, including single images, multi-view images, and video. In pursuit of minimal modeling, DA3 reveals two key insights: 💎 A plain transformer (e.g., vanilla DINO) is enough. No specialized architecture. ✨ A single depth-ray representation is enough. No complex 3D tasks. Three series of models have been released: the main DA3 series, a monocular metric estimation series, and a monocular depth estimation series. The core team members, aside from me: Haotong Lin, Sili Chen, Jun Hao Liew, Donny Y. Chen. 👇(1/n) #DepthAnything3

Bingyi Kang

516,444 görüntüleme • 11 ay önce

“She’s made a tough skill look easy there!” 👏 Our coaches provide in-depth analysis of Sophie Aitken's stunning half-time strike 👏 #WatfordFC | @mrqbingo

“She’s made a tough skill look easy there!” 👏 Our coaches provide in-depth analysis of Sophie Aitken's stunning half-time strike 👏 #WatfordFC | @mrqbingo

Watford Football Club

12,146 görüntüleme • 1 yıl önce

Excited to share our work InfiniDepth (CVPR 2026) — casting monocular depth estimation as a neural implicit field, which enables: 🔍 Arbitrary-Resolution 📐 Accurate Metric Depth 📷 Large-View Novel View Synthesis Feel free to try our code:

Excited to share our work InfiniDepth (CVPR 2026) — casting monocular depth estimation as a neural implicit field, which enables: 🔍 Arbitrary-Resolution 📐 Accurate Metric Depth 📷 Large-View Novel View Synthesis Feel free to try our code:

Sida Peng

39,053 görüntüleme • 7 ay önce

Wally has made roughly $28 million in his career and he’s saved every penny of it, by my estimation.

Wally has made roughly $28 million in his career and he’s saved every penny of it, by my estimation.

Jared Carrabis

80,409 görüntüleme • 8 ay önce