AI RESEARCH
Lite3R: A Model-Agnostic Framework for Efficient Feed-Forward 3D Reconstruction
arXiv CS.CV
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ArXi:2605.11354v1 Announce Type: new Transformer-based 3D reconstruction has emerged as a powerful paradigm for recovering geometry and appearance from multi-view observations, offering strong performance across challenging visual conditions. As these models scale to larger backbones and higher-resolution inputs, improving their efficiency becomes increasingly important for practical deployment.