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PixWorld Unifying 3D Scene Generation and Reconstruction in Pixel Space

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AK

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16,504 görüntüleme • 17 gün önce •via X (Twitter)

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Pixel-perfect 3D generation is here. 🧵 Tencent’s new Free Local Pixal3D project every pixel directly into 3D space. No more "AI hallucinations"—just sub-pixel faithful reconstruction. ✅ Open Weights ✅ Local (24GB VRAM) ✅ Matches silhouettes perfectly Is this the new benchmark for open-source 3D? Full workflow and test: 👇 #3DAI #Pixal3D #GameDev #Tencen #OpenSource #3DModeling
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Pixel-perfect 3D generation is here. 🧵 Tencent’s new Free Local Pixal3D project every pixel directly into 3D space. No more "AI hallucinations"—just sub-pixel faithful reconstruction. ✅ Open Weights ✅ Local (24GB VRAM) ✅ Matches silhouettes perfectly Is this the new benchmark for open-source 3D? Full workflow and test: 👇 #3DAI #Pixal3D #GameDev #Tencen #OpenSource #3DModeling

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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

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3D controllable video generation works well now and pixel alignment is impressive! We took our new 3D sculpt model, generated a blender scene and then asked a video-to-video model to render. Image to 3D sculpt: Common Sense Machines Synthetic rendering: Blender 🔶 Video-to-Video: Runway

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