TripoSR: Fast 3D Object Reconstruction from a Single Image
Dmitry Tochilkin11{}^{1}start_FLOATSUPERSCRIPT 1 end_FLOATSUPERSCRIPT David Pankratz11{}^{1}start_FLOATSUPERSCRIPT 1 end_FLOATSUPERSCRIPT Zexiang Liu22{}^{2}start_FLOATSUPERSCRIPT 2 end_FLOATSUPERSCRIPT Zixuan Huang11{}^{1}start_FLOATSUPERSCRIPT 1 end_FLOATSUPERSCRIPT Adam Letts11{}^{1}start_FLOATSUPERSCRIPT 1 end_FLOATSUPERSCRIPT Yangguang Li22{}^{2}start_FLOATSUPERSCRIPT 2 end_FLOATSUPERSCRIPT Ding Liang22{}^{2}start_FLOATSUPERSCRIPT 2 end_FLOATSUPERSCRIPT Christian Laforte11{}^{1}start_FLOATSUPERSCRIPT 1 end_FLOATSUPERSCRIPT Varun Jampani1*1{}^{1*}start_FLOATSUPERSCRIPT 1 * end_FLOATSUPERSCRIPT Yan-Pei Cao2*2{}^{2*}start_FLOATSUPERSCRIPT 2 * end_FLOATSUPERSCRIPT 11{}^{1}start_FLOATSUPERSCRIPT 1 end_FLOATSUPERSCRIPTStability AI, 22{}^{2}start_FLOATSUPERSCRIPT 2 end_FLOATSUPERSCRIPTTripo 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 [11] 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.
原文 arXiv:2403.02151;中英对照 + 大白话阅读 https://aha.fim.ai/paper/2403.02151v1