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📢GaussianGPT (ECCV'26) Code Release📢 What if 3D scenes worked like language? Generate full 3D Gaussian scenes - from scratch or from partial - token by token! 🔗 🌐 Great work by Nicolas von Lützow, Barbara Roessle, Katharina Schmid

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Matthias Niessner

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53,841 görüntüleme • 4 gün önce •via X (Twitter)

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📢GaussianGPT: autoregressive 3D Gaussian scene generation. We introduce a GPT-style model that directly generates 3D Gaussian scenes, token by token, in a series of small, discrete decision steps. Generation, completion, and large-scale outpainting in a single pipeline. Unlike diffusion-based approaches, GaussianGPT explicitly models the scene distribution at every step, allowing for quite flexible scene synthesis. 🌐 ▶️ Great work by Nicolas von Lützow, Barbara Roessle, Katharina Schmid
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📢GaussianGPT: autoregressive 3D Gaussian scene generation. We introduce a GPT-style model that directly generates 3D Gaussian scenes, token by token, in a series of small, discrete decision steps. Generation, completion, and large-scale outpainting in a single pipeline. Unlike diffusion-based approaches, GaussianGPT explicitly models the scene distribution at every step, allowing for quite flexible scene synthesis. 🌐 ▶️ Great work by Nicolas von Lützow, Barbara Roessle, Katharina Schmid

Matthias Niessner

152,004 görüntüleme • 3 ay önce

📢 GenRecon Code Release 📢 Few images in → complete, high-fidelity 3D scene out! GenRecon builds a generative prior on full scenes, resulting in unprecedented 3D reconstruction quality. 🔗 🌐 📄
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📢 GenRecon Code Release 📢 Few images in → complete, high-fidelity 3D scene out! GenRecon builds a generative prior on full scenes, resulting in unprecedented 3D reconstruction quality. 🔗 🌐 📄

Matthias Niessner

38,896 görüntüleme • 10 gün önce

📢📢GenRecon: Bridging Generative Priors for Multi-View 3D Scene Reconstruction📢📢 Reconstructing high-fidelity 3D scenes from sparse RGB input is hard. It needs a strong 3D prior! We reformulate multi-view scene reconstruction as conditional 3D generation over overlapping spatial chunks, lifting posed image features into a generative shape prior via 3D conditioning. As an example prior, we build on Trellis2, and train it such that its reconstruction is pixel aligned and matches from all views. GenRecon achieves unprecedented reconstruction quality from any sparse RGB input sequence, even from a phone capture. The reconstruction also includes PBR materials which facilitates relighting and virtual object insertion. Amazing work by Katharina Schmid, Nicolas von Lützow, Jozef, Angela Dai
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📢📢GenRecon: Bridging Generative Priors for Multi-View 3D Scene Reconstruction📢📢 Reconstructing high-fidelity 3D scenes from sparse RGB input is hard. It needs a strong 3D prior! We reformulate multi-view scene reconstruction as conditional 3D generation over overlapping spatial chunks, lifting posed image features into a generative shape prior via 3D conditioning. As an example prior, we build on Trellis2, and train it such that its reconstruction is pixel aligned and matches from all views. GenRecon achieves unprecedented reconstruction quality from any sparse RGB input sequence, even from a phone capture. The reconstruction also includes PBR materials which facilitates relighting and virtual object insertion. Amazing work by Katharina Schmid, Nicolas von Lützow, Jozef, Angela Dai

Matthias Niessner

17,999 görüntüleme • 1 ay önce

HoloDreamer can generate enclosed 3D scenes from text descriptions! It does so by first creating a high-quality equirectangular panorama and then rapidly reconstructing the 3D scene using 3D Gaussian Splatting. Links ⬇️
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HoloDreamer can generate enclosed 3D scenes from text descriptions! It does so by first creating a high-quality equirectangular panorama and then rapidly reconstructing the 3D scene using 3D Gaussian Splatting. Links ⬇️

Dreaming Tulpa 🥓👑

59,361 görüntüleme • 1 yıl önce

📢 LinPrim: Linear Primitives for Differentiable Volumetric Rendering 📢 We use octahedra or tetrahedra as explicit as volumetric building blocks for gradient-based novel view synthesis - as an alternative to 3D Gaussians with discrete, bounded geometry. We show how it can be used to reconstruct photorealistic scenes, and introduce a corresponding differentiable CUDA rasterizer that enables real-time rendering. On real-world scenes, LinPrim achieves comparable image quality with fewer primitives, adding a practical polyhedral option to the 3D scene representation toolbox and expanding the known design space. 🌍 🎥 Amazing work by Nicolas von Lützow!
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📢 LinPrim: Linear Primitives for Differentiable Volumetric Rendering 📢 We use octahedra or tetrahedra as explicit as volumetric building blocks for gradient-based novel view synthesis - as an alternative to 3D Gaussians with discrete, bounded geometry. We show how it can be used to reconstruct photorealistic scenes, and introduce a corresponding differentiable CUDA rasterizer that enables real-time rendering. On real-world scenes, LinPrim achieves comparable image quality with fewer primitives, adding a practical polyhedral option to the 3D scene representation toolbox and expanding the known design space. 🌍 🎥 Amazing work by Nicolas von Lützow!

Matthias Niessner

11,413 görüntüleme • 1 yıl önce

📢𝐋𝟑𝐃𝐆: 𝐋𝐚𝐭𝐞𝐧𝐭 𝟑𝐃 𝐆𝐚𝐮𝐬𝐬𝐢𝐚𝐧 𝐃𝐢𝐟𝐟𝐮𝐬𝐢𝐨𝐧📢 #SIGGRAPHAsia We propose a generative diffusion model for 3D Gaussians. Key is a learnt latent space which substantially reduces the complexity of the diffusion process, thus facilitating room-scale scene generation! Great work by Barbara Roessle in with Norman Müller, Angela Dai, Lorenzo Porzi, Samuel Rota Bulò, Peter Kontschieder!
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📢𝐋𝟑𝐃𝐆: 𝐋𝐚𝐭𝐞𝐧𝐭 𝟑𝐃 𝐆𝐚𝐮𝐬𝐬𝐢𝐚𝐧 𝐃𝐢𝐟𝐟𝐮𝐬𝐢𝐨𝐧📢 #SIGGRAPHAsia We propose a generative diffusion model for 3D Gaussians. Key is a learnt latent space which substantially reduces the complexity of the diffusion process, thus facilitating room-scale scene generation! Great work by Barbara Roessle in with Norman Müller, Angela Dai, Lorenzo Porzi, Samuel Rota Bulò, Peter Kontschieder!

Matthias Niessner

39,496 görüntüleme • 1 yıl önce

Gemini 3.0 Pro is at great 3D design and front-end. It can generate complex 3D scenes and Three.js objects from text prompts. Here's a nice retro-future example from cris.
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Gemini 3.0 Pro is at great 3D design and front-end. It can generate complex 3D scenes and Three.js objects from text prompts. Here's a nice retro-future example from cris.

Addy Osmani

90,189 görüntüleme • 6 ay önce

📢WorldMesh is accepted to #ECCV2026, and we're releasing the code today! 🎉 Led by mschneider456: navigable, multi-room 3D scenes from a text prompt, with a mesh scaffold conditioning image diffusion for global consistency + photorealistic detail 👇
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📢WorldMesh is accepted to #ECCV2026, and we're releasing the code today! 🎉 Led by mschneider456: navigable, multi-room 3D scenes from a text prompt, with a mesh scaffold conditioning image diffusion for global consistency + photorealistic detail 👇

Angela Dai

41,126 görüntüleme • 8 gün önce

📢 FaceAnything (ECCV 2026) Code Release 📢 Turn any image sequence into high-fidelity 4D face reconstructions, without controlled capture rigs. Try it on Hugging Face & reconstruct your face in 4D! 🔗 🤗 🌐
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📢 FaceAnything (ECCV 2026) Code Release 📢 Turn any image sequence into high-fidelity 4D face reconstructions, without controlled capture rigs. Try it on Hugging Face & reconstruct your face in 4D! 🔗 🤗 🌐

Matthias Niessner

47,685 görüntüleme • 12 gün önce

PhysX-Anything: creates simulation-ready, articulated 3D assets from a single image; VLM-based model using a new 3D representation that reduces token count by 193x
1:01

PhysX-Anything: creates simulation-ready, articulated 3D assets from a single image; VLM-based model using a new 3D representation that reduces token count by 193x

Wildminder

49,884 görüntüleme • 7 ay önce

📢 A Recipe for Generating 3D Worlds From a Single Image 📢 Our recipe explains how existing generative models can be adapted with minimal training effort to generate 3D worlds from a single input image.
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📢 A Recipe for Generating 3D Worlds From a Single Image 📢 Our recipe explains how existing generative models can be adapted with minimal training effort to generate 3D worlds from a single input image.

Katja Schwarz

13,970 görüntüleme • 1 yıl önce

📢 Intrinsic Image Fusion for Multi-View 3D Material Reconstruction 📢 We combine generative material priors with inverse path tracing: 1) define a parametric texture space 2) fuse monocular predictions across views into consistent textures 3) optimize low-dimensional parameters for physically-grounded reconstructions. The results are relightable PBR textures for 3D scenes: check out the result on a real-world 3D scan from the ScanNet++ dataset! 🌍 🎥 Great work by Peter Kocsis Lukas Höllein!
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📢 Intrinsic Image Fusion for Multi-View 3D Material Reconstruction 📢 We combine generative material priors with inverse path tracing: 1) define a parametric texture space 2) fuse monocular predictions across views into consistent textures 3) optimize low-dimensional parameters for physically-grounded reconstructions. The results are relightable PBR textures for 3D scenes: check out the result on a real-world 3D scan from the ScanNet++ dataset! 🌍 🎥 Great work by Peter Kocsis Lukas Höllein!

Matthias Niessner

23,087 görüntüleme • 6 ay önce

HUGE NEWS for 3D Gaussian Splatting! 📢 The PlayCanvas Engine adopts SOGS for 20x Compression of 3DGS. 🗜️ Load HUGE splat scenes even on mobile! 📱 Read More:
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HUGE NEWS for 3D Gaussian Splatting! 📢 The PlayCanvas Engine adopts SOGS for 20x Compression of 3DGS. 🗜️ Load HUGE splat scenes even on mobile! 📱 Read More:

PlayCanvas

22,664 görüntüleme • 1 yıl önce

📢Animating the Uncaptured 📢 We animate 3D humanoid meshes using video diffusion priors given a text prompt. 🎥 🌍 Realistic motion generation for 3D characters - without motion capture! 🚀 Great work by Marc Benedí Angela Dai
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📢Animating the Uncaptured 📢 We animate 3D humanoid meshes using video diffusion priors given a text prompt. 🎥 🌍 Realistic motion generation for 3D characters - without motion capture! 🚀 Great work by Marc Benedí Angela Dai

Matthias Niessner

11,704 görüntüleme • 1 yıl önce

ChatGPT Image arrived to Krea. edit images in Chat, render 3D scenes in Stage, or generate images from hundreds of Krea styles. more coming soon!
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ChatGPT Image arrived to Krea. edit images in Chat, render 3D scenes in Stage, or generate images from hundreds of Krea styles. more coming soon!

KREA AI

112,657 görüntüleme • 1 yıl önce

Robots that navigate grocery stores with semantic 3D maps created by language-augmented gaussian splats
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Robots that navigate grocery stores with semantic 3D maps created by language-augmented gaussian splats

Towaki Takikawa / 瀧川永遠希

48,814 görüntüleme • 10 ay önce

Turning movies shots into 3D scenes using 3D Gaussian Splats 🤯 Next experiment will be about taking footages from movies, turning them in 3D and then take them into Unreal Engine to add/edit. Remember this scene ?
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Turning movies shots into 3D scenes using 3D Gaussian Splats 🤯 Next experiment will be about taking footages from movies, turning them in 3D and then take them into Unreal Engine to add/edit. Remember this scene ?

Bad Decisions Studio

742,926 görüntüleme • 2 yıl önce

Wow. No more waiting hours for COLMAP / SfM — you get live 3D Gaussian Splats straight from unposed images, even for massive scenes. Your 3D scene and camera poses are ready right as you finish capturing. Inria team cooked again; code drops end of May.
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Wow. No more waiting hours for COLMAP / SfM — you get live 3D Gaussian Splats straight from unposed images, even for massive scenes. Your 3D scene and camera poses are ready right as you finish capturing. Inria team cooked again; code drops end of May.

Bilawal Sidhu

48,480 görüntüleme • 1 yıl önce

How to add fog to your 3D scenes from the Compositor in Blender by Daniel Nees. Master Compositing in Blender Course: #b3d #blender3d #compositing #3dart #vfx #3d
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How to add fog to your 3D scenes from the Compositor in Blender by Daniel Nees. Master Compositing in Blender Course: #b3d #blender3d #compositing #3dart #vfx #3d

CG Boost

28,600 görüntüleme • 9 ay önce