Figure 2. Training pipeline of NAS3R. Subscripts “C ” and “T ” denote context and target views, respectively. Unconstrained images are
patchified into visual tokens and concatenated with a learnable camera token for camera prediction. A masked decoder regulates cross-view
interactions and prevents target-to-context leakage. Refined context tokens are then processed by the Gaussian head to predict Gaussian
parameters, while a depth head estimates depth maps that are lifted into 3D Gaussian centers using the predicted context poses. The
predicted target poses are finally used to render novel views, providing photometric supervision for end-to-end training.