4DGS360: 360deg Gaussian Reconstruction of Dynamic Objects from a Single Video

We introduce 4DGS360, a diffusion-free framework for 360circ dynamic object reconstruction from casual monocular video. Existing methods often fail to reconstruct consistent 360circ geometry, as their heavy reliance on 2D-native priors causes initial points to overfit to visible surface in each training view. 4DGS360 addresses this challenge through a advanced 3D-native initialization that mitigates the geometric ambiguity of occluded regions. Our proposed 3D tracker, AnchorTAP3D, produces reinforced 3D point trajectories by leveraging confident 2D track points as anchors, suppressing drift and providing reliable initialization that preserves geometry in occluded regions. This initialization, combined with optimization, yields coherent 360circ 4D reconstructions. We further present iPhone360, a new benchmark where test cameras are placed up to 135circ apart from training views, enabling 360circ evaluation that existing datasets cannot provide. Experiments show that 4DGS360 achieves state-of-the-art performance on the iPhone360, iPhone, and DAVIS datasets, both qualitatively and quantitatively.