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CVPR2026Top-tier venue

2D-LFM: Lifting Foundation Model without 3D Supervision

Mosam Dabhi, Irhas Gill, László A. Jeni, Simon Lucey

2026Year

Abstract

Figure 1. 2D landmark lifting without 3D supervision matches supervised methods. Given 2D keypoints from single images (top), we compare against VGGT [19] which back-projects through predicted depth (middle) versus our 2D-LFM trained with 2D supervision only (bottom). VGGT produces distorted geometry despite accurate scene depth (> 100mm MPJPE), while 2D-LFM recovers correct object structure (8.1mm). Ground truth: red, Predictions: blue.

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