TripoSR: Fast 3D Object Reconstruction from a Single Image

Dmitry Tochilkin, David Pankratz, Zexiang Liu, Zixuan Huang, Adam Letts, Yangguang, dingliang, Christian Laforte, Varun Jampani, Yanpei Cao

TripoSR: Fast 3D Object Reconstruction from a Single Image: 15 upvotes on Hugging Face Daily Papers, #7 of 11 papers on 2024-03-05. Day-by-day upvote history.

This technical report introduces TripoSR, a 3D reconstruction model leveraging transformer architecture for fast feed-forward 3D generation, producing 3D mesh from a single image in under 0.5 seconds. Building upon the LRM network architecture, TripoSR integrates substantial improvements in data processing, model design, and training techniques. Evaluations on public datasets show that TripoSR exhibits superior performance, both quantitatively and qualitatively, compared to other open-source alternatives. Released under the MIT license, TripoSR is intended to empower researchers, developers, and creatives with the latest advancements in 3D generative AI.

Paper page on Hugging Face · arXiv

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