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Paper · arXiv 2403.02151

TripoSR: Fast 3D Object Reconstruction from a Single Image

Dmitry Tochilkin, David Pankratz, Zexiang Liu, Zixuan Huang, Adam Letts, Yangguang Li, Ding Liang, Christian Laforte, Varun Jampani, Yan-Pei Cao

15 upvotesMarch 4, 2024arXiv 预印本
AI 摘要

TripoSR, a 3D reconstruction model using transformer architecture, generates 3D meshes quickly from single images and outperforms alternatives.

transformer architecture3D reconstruction modelLRM networkfeed-forward 3D generation3D meshpublic datasetsMIT license3D generative AI

Abstract

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.

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