Dense Dynamic Scene Reconstruction and Camera Pose Estimation from Multi-View Videos
The work proposes a two-stage optimization framework to reconstruct dense, dynamic scenes from multiple free cameras. It combines robust camera tracking using a spatio-temporal connection graph with a wide-baseline initialization strategy. This allows for accurate per-frame camera pose estimation and dense depth refinement across the entire scene, overcoming scale ambiguity and limited overlap challenges.