PixARMesh: Autoregressive Mesh-Native Single-View Scene Reconstruction
We introduce PixARMesh, a method to autoregressively reconstruct complete 3D indoor scene meshes directly from a single RGB image. Unlike prior methods that rely on implicit signed distance fields and post-hoc layout optimization, PixARMesh jointly predicts object layout and geometry within a unified model, producing coherent and artist-ready meshes in a single forward pass. Building on recent advances in mesh generative models, we augment a point-cloud encoder with pixel-aligned image features and global scene context via cross-attention, enabling accurate spatial reasoning from a single image. Scenes are generated autoregressively from a unified token stream containing context, pose, and mesh, yielding compact meshes with high-fidelity geometry. Experiments on synthetic and real-world datasets show that PixARMesh achieves state-of-the-art reconstruction quality while producing lightweight, high-quality meshes ready for downstream applications.
69ae25219893f58272f7406b
Xiang Zhang
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2026-03-09T08:48:07.643Z
679da97f2000f0eecaaa8e9c
/avatars/646128f0629143f05d6496cc93719184.svg
Xiang Zhang
zx1239856
user
zx1239856
69ae25219893f58272f7406c
Sohyun Yoo
69ae25219893f58272f7406d
Hongrui Wu
69ae25219893f58272f7406e
Chuan Li
69ae25219893f58272f7406f
Jianwen Xie
69ae25219893f58272f74070
Zhuowen Tu
PixARMesh: Autoregressive Mesh-Native Single-View Scene Reconstruction
We introduce PixARMesh, a method to autoregressively reconstruct complete 3D indoor scene meshes directly from a single RGB image. Unlike prior methods that rely on implicit signed distance fields and post-hoc layout optimization, PixARMesh jointly predicts object layout and geometry within a unified model, producing coherent and artist-ready meshes in a single forward pass. Building on recent advances in mesh generative models, we augment a point-cloud encoder with pixel-aligned image features and global scene context via cross-attention, enabling accurate spatial reasoning from a single image. Scenes are generated autoregressively from a unified token stream containing context, pose, and mesh, yielding compact meshes with high-fidelity geometry. Experiments on synthetic and real-world datasets show that PixARMesh achieves state-of-the-art reconstruction quality while producing lightweight, high-quality meshes ready for downstream applications.
PixARMesh enables end-to-end 3D indoor scene mesh reconstruction from single RGB images using a unified model with cross-attention and autoregressive token generation.
mesh generative models cross-attention autoregressive token stream point-cloud encoder pixel-aligned features scene reconstruction