ParaScale: Scale-Calibrated Camera-Motion Transfer via a Gauge-Invariant Parallax Number
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Abstract (arXiv)
Transferring the camera motion of a reference video to a freshly generated one lets creators reuse cinematic moves. Yet reference and target often live at incompatible scales -- a sweep across a galaxy versus a nudge across a desk -- and naively reusing the recovered trajectory yields either imperceptible or violently exaggerated motion. We trace this to a geometric fact: translation-induced image motion scales as ||T||/Z, so a monocular trajectory is meaningful only up to a depth-scale gauge. We distill this into the Parallax Number Pi = ||Delta T|| / Zbar, a dimensionless, gauge-invariant descriptor of how strongly a camera move is felt, and prove that it -- not the raw trajectory -- is the quantity that scale-faithful transfer must preserve. ParaScale is a plug-and-play module that reads Pi off any reference video and re-realizes it against the target scene's own depth, per frame, leaving rotation untouched. Sitting between pose extraction and pose injection, it requires no retraining and drops into any pose-conditioned generator. We further introduce the Parallax Consistency Error (PCE), a scale-symmetric metric that -- unlike the similarity-aligned TransErr -- exposes scene-scale mismatch. Across scale regimes spanning four orders of magnitude and multiple backbones, ParaScale keeps the realized parallax on the identity line and cuts PCE by more than 3x over uncalibrated transfer with no loss of visual fidelity.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 19 of its 25 references that are in the map. First posted on arXiv 18 Jun 2026.
Builds on
19 of 25 references.
References · 19
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- 2025Wan: Open and Advanced Large-Scale Video Generative Modelscited by 2,708
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- 2021DriveGAN: Towards a Controllable High-Quality Neural Simulationcited by 125
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- 2025MagicMotion: Controllable Video Generation with Dense-to-Sparse Trajectory Guidancecited by 61
- 2024MotionMaster: Training-free Camera Motion Transfer For Video Generationcited by 51
7 more
- 2024DiVE: DiT-based Video Generation with Enhanced Controlcited by 31
- 2024DriveScape: Towards High-Resolution Controllable Multi-View Driving Video Generationcited by 22
- 2025Generating Multimodal Driving Scenes via Next-Scene Predictioncited by 12
- 2025SynPo: Boosting Training-Free Few-Shot Medical Segmentation via High-Quality Negative Promptscited by 9
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- 2026OmniDirector: General Multi-Shot Camera Cloning without Cross-Paired Datacited by 6
- 2026TRIDENT: Breaking the Hybrid-Safety-Physics Coupling for Provably Safe Multi-Agent Reinforcement Learningcited by 2
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Citing papers per year: 2026: 2.
2 papers.