LongReplay: Exporable Long Video Reshooting with Dynamic Memory

Camera-controlled video reshooting synthesizes a novel-view video along a user-specified camera trajectory while remaining temporally synchronized with a source recording. Existing methods operate on short clips, where the source and the target occupy one attention window. We study long-video reshooting, in which the source may span minutes and the target is generated autoregressively in overlapping chunks. This setting requires synchronization under large camera baselines and large subject motion, together with long-term 3D consistency of the static scene and semantic consistency of dynamic subjects. Our key insight is to query a dynamic memory of the source video along time, space, and semantics. We propose LongReplay, which realizes this readout in two stages with dynamic-awareness. Memory selection retrieves a synchronized source chunk, multi-time spatial patches that cover the target field of view, and semantic anchors that store subject frames independently of the queried time and location. Dynamic-aware correspondence then identifies retrieved patches jointly by time and space with a 4D projection embedding, and matches tokens by semantics with TIPS descriptors. Supervising these queries requires paired long videos of the same dynamic scene under different cameras, so we construct WorldReplay, a Unreal Engine 5 pipeline that renders multiple camera trajectories in the same long take. Experiments show improved multi-view synchronization, including under large viewpoint changes, together with long-range geometric and identity consistency, relative to baselines.