Lift4D reconstructs non-rigid 4D objects from single-view video

// 1h agoRESEARCH PAPER

Lift4D reconstructs non-rigid 4D objects from single-view video

Lift4D introduces a framework for reconstructing dynamic, non-rigid objects from monocular in-the-wild video. By adapting single-view 3D models with causal latent conditioning and utilizing deformable 3D Gaussian Splatting, it generates temporally consistent 4D representations even under severe occlusions.

// ANALYSIS

Lift4D tackles one of the hardest problems in generative vision by achieving coherent 4D object reconstruction from a single moving camera without massive 4D training datasets.

–Causal latent conditioning adapts existing single-view 3D models to produce temporally consistent per-frame predictions
–Deformable 3D Gaussian Splatting efficiently models complex non-rigid motion and appearance over time
–An occlusion-aware optimization paired with a view-conditioned diffusion prior intelligently hallucinates unseen regions

// TAGS

lift4d3d-genvideo-genvisionresearch

DISCOVERED

1h ago

2026-06-25

PUBLISHED

1d ago

2026-06-23

RELEVANCE

8/ 10

AUTHOR

_akhaliq

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