Create

Sign in to ReadmeX

or

How we handle your data: Privacy Policy

ReadmeX

Your AI reading companion

What would you like to catch up on?

Pick a briefing, or ask your own question.

Your community and people briefings stay personal to you.

WorldRecon

AI overview

Sign in and the AI will write an overview from our coverage.

Headlines · 1

  1. WorldRecon: Generative multi-view mesh reconstruction for large-scale 3D scenes

    A new arXiv paper introduces WorldRecon, a generative multi-view reconstruction framework that recovers complete, large-scale 3D scene meshes from unposed RGB images. It uses a coarse, noisy global point cloud and camera poses estimated from the inputs as a global scaffold, partitions the scene into overlapping spatial blocks, and equips the native 3D generative model TRELLIS.2 with reconstruction-based conditioning to produce sparse structure, detailed geometry and PBR materials from each block's local point-cloud crop and relevant image observations. To keep scenes coherent, the authors add neighbour-aware latent inpainting and a causal world-generation procedure that propagates structural, geometric and material context across blocks. The paper reports state-of-the-art results, reducing Chamfer distance by 14.9% and 43.1% and improving F-score by 17.3% and 12.0% over the strongest baselines on synthetic and real-world indoor scenes respectively, with strong claimed sim-to-real generalization.

    Hugging Face · Papers · 🔥 0

Experience and discussion from the community

Share my WorldRecon experienceAsk about WorldRecon

Nobody has shared their experience with WorldRecon yet.