Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

Excited to share our recent work, UniSH, which unifies dynamic 3D scene reconstruction and SMPL estimation within a single framework. (Left-top is input video). Code has been released! Project page: Paper:

YuanLiu41955461's profile picture

Yuan Liu

2,009 subscribers

19,242 görüntüleme • 6 ay önce •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

I'm excited to share our new work, VistaDream, which generates a 3D Gaussian field from a single-view image. The codes have already been released. Project page: (with interactive demos) Code: Paper:
0:27

I'm excited to share our new work, VistaDream, which generates a 3D Gaussian field from a single-view image. The codes have already been released. Project page: (with interactive demos) Code: Paper:

Yuan Liu

79,592 görüntüleme • 1 yıl önce

I'm excited to share our new work Align3R that estimates camera poses and consistent depth maps from a monocular video of a dynamic scene. Project page: Code: Paper:
1:12

I'm excited to share our new work Align3R that estimates camera poses and consistent depth maps from a monocular video of a dynamic scene. Project page: Code: Paper:

Yuan Liu

56,547 görüntüleme • 1 yıl önce

Feed-forward 3D Gaussians from Visual Geometry Group (VGG) strike again! Flash3D has now been accepted to 3DV 2025: it is a method for feed-forward single-view 3D scene reconstruction. Project page: Code: Arxiv: A 🧵👇
0:27

Feed-forward 3D Gaussians from Visual Geometry Group (VGG) strike again! Flash3D has now been accepted to 3DV 2025: it is a method for feed-forward single-view 3D scene reconstruction. Project page: Code: Arxiv: A 🧵👇

Stan Szymanowicz

26,970 görüntüleme • 1 yıl önce

Our new work PSHuman reconstructs a detailed 3D human mesh from a single-view image in ~1min. Codes have already been released! Welcome to try it! Project page: Codes: Paper:
0:39

Our new work PSHuman reconstructs a detailed 3D human mesh from a single-view image in ~1min. Codes have already been released! Welcome to try it! Project page: Codes: Paper:

Yuan Liu

53,252 görüntüleme • 1 yıl önce

🚀Turn Single Image into 3D Human🚀 #GeneMAN is a generalizable single-image 3D human reconstruction framework that turns in-the-wild images into high-quality 3D humans with ease 🔗Project: 📜Paper: 🧑‍💻Code:
1:04

🚀Turn Single Image into 3D Human🚀 #GeneMAN is a generalizable single-image 3D human reconstruction framework that turns in-the-wild images into high-quality 3D humans with ease 🔗Project: 📜Paper: 🧑‍💻Code:

Ziwei Liu

26,953 görüntüleme • 1 yıl önce

Happy to share our new work, MVInverse, a feedforward framework for multiview PBR material estimation at ~10 fps. Multiview ViT (like VGGT, Pi3) can also do material estimation! Paper: Homepage: Code:
1:04

Happy to share our new work, MVInverse, a feedforward framework for multiview PBR material estimation at ~10 fps. Multiview ViT (like VGGT, Pi3) can also do material estimation! Paper: Homepage: Code:

Yuan Liu

11,933 görüntüleme • 6 ay önce

Excited to share Track4World, feedforward 3D tracking of all pixels in the world-centric coordinate system. Code has been released, and welcome to try it! Homepage: Code: Paper:
1:42

Excited to share Track4World, feedforward 3D tracking of all pixels in the world-centric coordinate system. Code has been released, and welcome to try it! Homepage: Code: Paper:

Yuan Liu

20,054 görüntüleme • 4 ay önce

(1/4) Excited to share our #ICCV2023 paper Text2Room! We generate scene-scale textured 3D meshes from a given text prompt leveraging 2D text-to-image models such as StableDiffusion. Project: Code: Video:
0:24

(1/4) Excited to share our #ICCV2023 paper Text2Room! We generate scene-scale textured 3D meshes from a given text prompt leveraging 2D text-to-image models such as StableDiffusion. Project: Code: Video:

Matthias Niessner

74,895 görüntüleme • 3 yıl önce

📢 Lyra: Generative 3D Scene Reconstruction via Video Diffusion Model Self-Distillation Got only one or a few images and wondering if recovering the 3D environment is a reconstruction or generation problem? Why not do it with a generative reconstruction model! We show that a camera-conditioned video diffusion model can be transformed into a generative reconstruction model that directly outputs a high-quality 3D Gaussian Splatting representation through self-distillation, without requiring real-world training data. Check out our results in the video (wait for dynamic scenes in the second half!) : Project Page: Code and Models: Paper:
0:50

📢 Lyra: Generative 3D Scene Reconstruction via Video Diffusion Model Self-Distillation Got only one or a few images and wondering if recovering the 3D environment is a reconstruction or generation problem? Why not do it with a generative reconstruction model! We show that a camera-conditioned video diffusion model can be transformed into a generative reconstruction model that directly outputs a high-quality 3D Gaussian Splatting representation through self-distillation, without requiring real-world training data. Check out our results in the video (wait for dynamic scenes in the second half!) : Project Page: Code and Models: Paper:

Sherwin Bahmani

66,576 görüntüleme • 9 ay önce

Thrilled to share our new work on Reconviagen✨! A key challenge in 3D creation is the alignment of generative 3D with observational input. Our method solves this by grounding the generative process in 3D reconstruction. Try it at: #Reconstruction #AIGC
0:29

Thrilled to share our new work on Reconviagen✨! A key challenge in 3D creation is the alignment of generative 3D with observational input. Our method solves this by grounding the generative process in 3D reconstruction. Try it at: #Reconstruction #AIGC

Chongjie(CJ) Ye

11,614 görüntüleme • 10 ay önce

📢📢📢 Excited to share our new work *Autonomous Character-Scene Interaction Synthesis from Text Instruction* (Siggraph Asia 24). It presents a unified model for flexible scene-conditioned motion generation given text, scene, trajectory conditions. The results with smooth interaction look very impressive! 📰Paper: Project: Code and data will be released soon.
6:34

📢📢📢 Excited to share our new work *Autonomous Character-Scene Interaction Synthesis from Text Instruction* (Siggraph Asia 24). It presents a unified model for flexible scene-conditioned motion generation given text, scene, trajectory conditions. The results with smooth interaction look very impressive! 📰Paper: Project: Code and data will be released soon.

Siyuan Huang

11,340 görüntüleme • 1 yıl önce

Synthesia research releases HumanRF: High-Fidelity Neural Radiance Fields for Humans in Motion a 4D dynamic neural scene representation that captures full-body appearance in motion from multi-view video input, and enables playback from novel, unseen viewpoints project page: paper page:
3:06

Synthesia research releases HumanRF: High-Fidelity Neural Radiance Fields for Humans in Motion a 4D dynamic neural scene representation that captures full-body appearance in motion from multi-view video input, and enables playback from novel, unseen viewpoints project page: paper page:

AK

160,702 görüntüleme • 3 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:
0:34

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

38,787 görüntüleme • 3 ay önce

🚨 Paper Alert Our recent breakthrough CAST: Component-Aligned 3D Scene Reconstruction from an RGB Image has been accepted by ACM SIGGRAPH 2025 Journal Track! CAST will change the way create scenes in 3D Art and Embody AI. 🚀Soon available at 👇Details
3:41

🚨 Paper Alert Our recent breakthrough CAST: Component-Aligned 3D Scene Reconstruction from an RGB Image has been accepted by ACM SIGGRAPH 2025 Journal Track! CAST will change the way create scenes in 3D Art and Embody AI. 🚀Soon available at 👇Details

Deemos

34,110 görüntüleme • 1 yıl önce

Excited to share MonST3R! -- a simple way to estimate geometry from unposed video of dynamic scene We achieve competitive results on several downstreams (video depth, camera pose) and believe this is a promising step toward feed-forward 4D reconstruction
1:03

Excited to share MonST3R! -- a simple way to estimate geometry from unposed video of dynamic scene We achieve competitive results on several downstreams (video depth, camera pose) and believe this is a promising step toward feed-forward 4D reconstruction

Junyi Zhang

131,562 görüntüleme • 1 yıl önce

📢Introducing 360Anything, our method for lifting any perspective image or video to gravity-aligned 360° panoramas without using any camera or 3D information. This enables consistent novel view synthesis and 3D scene reconstruction. Project page: 🧵
1:05

📢Introducing 360Anything, our method for lifting any perspective image or video to gravity-aligned 360° panoramas without using any camera or 3D information. This enables consistent novel view synthesis and 3D scene reconstruction. Project page: 🧵

Ziyi Wu

62,310 görüntüleme • 5 ay önce

We’ve just open-sourced JOSH, our method for 4D human–scene reconstruction in the wild. Huge credit to the first author, my PhD student Zhizheng, who will present this work at ICLR in Brazil next month 🇧🇷 🌐 Project page: 💻 Code: A trivia is that this work was finished more than one year ago, and has been rejected twice...Be resilient!
0:25

We’ve just open-sourced JOSH, our method for 4D human–scene reconstruction in the wild. Huge credit to the first author, my PhD student Zhizheng, who will present this work at ICLR in Brazil next month 🇧🇷 🌐 Project page: 💻 Code: A trivia is that this work was finished more than one year ago, and has been rejected twice...Be resilient!

Bolei Zhou

25,521 görüntüleme • 4 ay önce

I'm excited to share our new work Diffusion as Shader (DaS), a versatile controllable video generation method for various tasks: object manipulation, camera control, mesh-to-video, and motion transfer. Project page: Github:
0:46

I'm excited to share our new work Diffusion as Shader (DaS), a versatile controllable video generation method for various tasks: object manipulation, camera control, mesh-to-video, and motion transfer. Project page: Github:

Yuan Liu

33,363 görüntüleme • 1 yıl önce

Excited to share SingSong, a system which can generate instrumental accompaniments to pair with input vocals! 📄 🔊 Work co-led by myself, Antoine Caillon, and Adam Roberts as part of Google Magenta Project and the broader MusicLM project 🧵
1:45

Excited to share SingSong, a system which can generate instrumental accompaniments to pair with input vocals! 📄 🔊 Work co-led by myself, Antoine Caillon, and Adam Roberts as part of Google Magenta Project and the broader MusicLM project 🧵

Chris Donahue

1,458,513 görüntüleme • 3 yıl önce

Extract accurate depth from your 3D gaussians! Fast, accurate, and easy to use. Code of RaDe-GS is released! project page: code: paper: No need to change your 3D GS representations, we propose a play-and-plug rasterizer to extract accurate depth and normal from 3D gaussians, leading to the possibility of high-quality geometry reconstruction. It's quite efficient and fast, achieving 0.69mm errors on DTU dataset in only 5 minutes. Very easy to adopt the rasterizer in your any 3dgs projects.
0:24

Extract accurate depth from your 3D gaussians! Fast, accurate, and easy to use. Code of RaDe-GS is released! project page: code: paper: No need to change your 3D GS representations, we propose a play-and-plug rasterizer to extract accurate depth and normal from 3D gaussians, leading to the possibility of high-quality geometry reconstruction. It's quite efficient and fast, achieving 0.69mm errors on DTU dataset in only 5 minutes. Very easy to adopt the rasterizer in your any 3dgs projects.

Xiao-Xiao Long

31,290 görüntüleme • 2 yıl önce