AI RESEARCH
VDPP: Video Depth Post-Processing for Speed and Scalability
arXiv CS.CV
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ArXi:2604.06665v1 Announce Type: new Video depth estimation is essential for providing 3D scene structure in applications ranging from autonomous driving to mixed reality. Current end-to-end video depth models have established state-of-the-art performance. Although current end-to-end (E2E) models have achieved state-of-the-art performance, they function as tightly coupled systems that suffer from a significant adaptation lag whenever superior single-image depth estimators are released.