AI RESEARCH
BA-T: An Iterative Transformer for Two-View Bundle Adjustment
arXiv CS.CV
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ArXi:2606.03287v1 Announce Type: new Feed-forward models for 3D reconstruction have achieved strong performance using deep cross-view attention to exchange information across images. However, these approaches often depend on heavy decoder stacks and lack a structured mechanism for geometry refinement, resulting in poor multi-view consistency. We address this by drawing inspiration from classical bundle adjustment (BA), which can be viewed as an iterative information propagation process between poses and local geometry.