CorrRetime: Correspondence-Guided Object-wise Space-Time Retiming

Recent video diffusion methods have explored temporal control, but typically apply a single global transformation to the entire scene, making it difficult to independently control the temporal evolution of multiple objects and the camera/background within the same video. We introduce CorrRetime, a controllable video diffusion framework for fine-grained object-wise temporal remapping with independent camera/background retiming. Our key idea is to represent this control through explicit spatiotemporal correspondences that specify, for each output frame, both the source-time state of each object and its target location under the retimed camera trajectory. This enables multiple foreground objects to independently accelerate, decelerate, pause, resume, or reverse while preserving their underlying source motion, while the camera/background can be independently retimed along the original camera path according to a separate temporal schedule. To enable supervised training and systematic evaluation of this task, we construct a large-scale synthetic dataset with independently parameterized object and camera temporal schedules, spanning diverse multi-object retiming patterns, camera trajectories, and occlusion relationships. We evaluate CorrRetime on both synthetic and real-world videos, demonstrating accurate object-wise and camera/background temporal control while outperforming adapted baselines in retiming accuracy and visual quality.