ART-VSR: Adaptive Rectified Trajectories for One-Step Video Super-Resolution

Generative priors have advanced VSR, yet their multi-step inference remains costly. Recent trajectory-based one-step VSR methods accelerate generation from low-resolution (LR) inputs, but can struggle under complex real-world degradations. We analyze this limitation as trajectory drift, caused by initial state mismatch and a global timestep constraint. We propose ART-VSR, a state-time adaptation framework that estimates a continuous token-wise timestep map with an Adaptive Timestep Estimator (ATE) and uses it to guide a Latent Trajectory Rectifier (LTR) toward a compatible starting state. Conditioned on the rectified latent and spatial timestep map, ARTVSR achieves highly competitive one-step VSR performance, producing crisp, artifact-reduced details while preserving temporal consistency. Code: https://github.com/Roveer/ART_VSR.